Publications and Presentations


Carmichael, D, Smees, R, Shillcock, RC & Simner, J 2018, 'Is there a burden attached to synaesthesia? Health screening of synaesthetes in the general population' British Journal of Psychology, pp. 1-19. DOI: 10.1111/bjop.12354

Riddell, S, Carmichael, D, Harris, N, Macallister, J & Wright, K CREID Briefing 40: Analysis of key informant interviews: Scotland.

Carmichael, D & Riddell, S CREID Briefing 39: Scottish local authority survey results.

Riddell, S, Carmichael, D, Harris, N, Macallister, J & Wright, K 2018 'Working Paper 5: Analysis of key informant interviews: Scotland' Centre for Research in Education Inclusion and Diversity (CREID), University of Edinburgh, Edinburgh, pp. 1-53.

Carmichael, D & Riddell, S 2018 'Working Paper 3: Scottish local authority survey results' Centre for Research in Education Inclusion and Diversity (CREID), University of Edinburgh, Edinburgh, pp. 1-35.

Carmichael, D & Riddell, S 2017 'Working paper 1: An overview of statistics on SEN in England and ASN in Scotland' Centre for Research in Education Inclusion and Diversity (CREID), University of Edinburgh, Edinburgh, pp. 1-51.

Mealor, AD, Simner, J, Rothen, N, Carmichael, D & Ward, J 2016, 'Different dimensions of cognitive style in typical and atypical cognition: New evidence and a new measurement tool' PLoS One, vol. 11, no. 5, pp. 1-21. DOI: 10.1371/journal.pone.0155483

Havlik, AM, Carmichael, D & Simner, J 2015, 'Do sequence-space synaesthetes have better spatial imagery skills? Yes, but there are individual differences' Cognitive Processing, vol. 16, no. 3, pp. 245-253. DOI: 10.1007/s10339-015-0657-1

Slocombe, R, Carmichael, D & Simner, J 2016, 'Cross-modal tactile–taste interactions in food evaluations' Neuropsychologia, vol. 88, pp. 58-64. DOI: 10.1016/j.neuropsychologia.2015.07.011

Simner, J, Rehme, MK, Carmichael, D, Bastin, M, Sprooten, E, McIntosh, A, Lawrie, S & Zedler, M 2016, 'Social responsiveness to inanimate entities: Altered white matter in a ‘social synaesthesia’' Neuropsychologia, vol. 91, pp. 282-289. DOI: 10.1016/j.neuropsychologia.2016.08.020

Simner, J & Carmichael, D 2015, 'Is synaesthesia a dominantly female trait?' Cognitive Neuroscience, pp. 1-9. DOI: 10.1080/17588928.2015.1019441

Carmichael, DA, Down, MP, Shillcock, RC, Eagleman, DM & Simner, J 2015, 'Validating a standardised test battery for synesthesia: Does the Synesthesia Battery reliably detect synesthesia?' Consciousness and Cognition, vol. 33, pp. 375-385. DOI: 10.1016/j.concog.2015.02.001

Kay, CL, Carmichael, D, Ruffell, HE & Simner, J 2014, 'Colour fluctuations in grapheme-colour synaesthesia: The effect of clinical and non-clinical mood changes' British Journal of Psychology. DOI: 10.1111/bjop.12102

Carmichael, DA, Shillcock, R & Simner, J 2014, 'Higher rates of anxiety found in self-reported grapheme-colour synaesthetes' UK Synaesthesia Association Annual Conference, London, United Kingdom, 12/04/14 - 13/04/14, .

Mealor, A, Carmichael, D, Simner, J & Ward, J 2014, 'The Sussex Cognitive Styles Questionnaire: An exploratory factor analysis in synaesthetes and controls' Synaesthesia in Perspective: Development, Networks, and Multisensory Processing, Hamburg, Germany, 28/02/14 - 1/03/14, .

Kucera, KS, Graham, S, Carmichael, D, Asher, JE, Chan, A, Murphy, L, Baron-Cohen, S, Simner, J & Fisher, SE 2014, 'Decoding the genetics of synaesthesia using state-of-the-art genomics' Synaesthesia in Perspective: Development, Networks, and Multisensory Processing, Hamburg, Germany, 28/02/14 - 1/03/14, .

Simner, J, Carmichael, D, Hubbard, EM, Morris, Z & Lawrie, SM 2014, 'Rates of white matter hyperintensities compatible with the radiological profile of multiple sclerosis within self-referred synesthete populations' Neurocase. DOI: 10.1080/13554794.2014.892625

Asher, JE & Carmichael, D 2013, The genetics and inheritance of synaesthesia. in J Simner & EM Hubbard (eds), Oxford Handbook of Synesthesia. Oxford University Press, pp. 23-45.

Carmichael, D & Simner, J 2013, 'The immune hypothesis of synesthesia' Frontiers in Human Neuroscience, vol. 7, 563. DOI: 10.3389/fnhum.2013.00563

Crowley, E, Gray, G & Storkey, A 2018, Moonshine: Distilling with Cheap Convolutions. in Thirty-second Conference on Neural Information Processing Systems (NIPS 2018). Thirty-second Conference on Neural Information Processing Systems, Montreal, Canada, 3/12/18.

Gray, G & Storkey, A 2016, 'Resource-Efficient Feature Gathering at Test Time' Reliable Machine Learning in the Wild, Barcelona, Spain, 9/12/16, .

Hilgen, G, Sindaci, MS, Pirmoradian, S, Muthmann, J-O, Kepiro, I, Ullo, S, Juarez Ramirez, C, Encinas, AP, Maccione, A, Berdondini, L, Murino, V, Sona, D, Cella Zanacchi, F, Sernagor, E & Hennig, MH 2017, 'Unsupervised spike sorting for large scale, high density multielectrode arrays' Cell Reports, vol. 18, no. 10, pp. 2521-2532. DOI: 10.1016/j.celrep.2017.02.038

Yoon, S, Sindaci, MS, Goltsev, AV & Mendes, JFF 2015, 'Critical behavior of the relaxation rate, the susceptibility, and a pair correlation function in the Kuramoto model on scale-free networks' Physical Review E, vol. 91, no. 3. DOI: 10.1103/PhysRevE.91.032814

Doncieux, S, Filliat, D, Diaz-Rodriguez, N, Hospedales, T, Duro, R, Coninx, A, M. Roijers, D, Girard, B, Perrin, N & Sigaud, O 2018, 'Open-Ended Learning: A Conceptual Framework Based on Representational Redescription' Frontiers in Neurorobotics, vol. 12, 59, pp. 1-6. DOI: 10.3389/fnbot.2018.00059

Hu, G, Liu, L, Yuan, Y, Yu, Z, Hua, Y, Zhang, Z, Shen, F, Shao, L, Hospedales, T, Robertson, N & Yang, Y 2018, Deep Multi-Task Learning to Recognise Subtle Facial Expressions of Mental States. in European Conference on Computer Vision (ECCV 2018). Springer, Cham, Munich, Germany, pp. 106-123, European Conference on Computer Vision 2018, Munich, Germany, 8/09/18. DOI: 10.1007/978-3-030-01258-8_7

Pang, K, Li, D, Song, J, Song, Y-Z, Xiang, T & Hospedales, T 2018, Deep Factorised Inverse-Sketching. in European Conference on Computer Vision (ECCV 2018). Springer, Cham, Munich, Germany, pp. 37-54, European Conference on Computer Vision 2018, Munich, Germany, 8/09/18. DOI: 10.1007/978-3-030-01267-0_3

Li, K, Pang, K, Song, J, Song, Y-Z, Xiang, T, Hospedales, T & Zhang, H 2018, Universal Sketch Perceptual Grouping. in European Conference on Computer Vision (ECCV 2018). Springer, Cham, Munich, Germany, pp. 593-609, European Conference on Computer Vision 2018, Munich, Germany, 8/09/18. DOI: 10.1007/978-3-030-01237-3_36

Pang, K, Dong, M, Wu, Y & Hospedales, T 2018, Dynamic Ensemble Active Learning: A Non-Stationary Bandit with Expert Advice. in Proceedings of the 2018 24th International Conference on Pattern Recognition (ICPR). IEEE, Beijing, China, pp. 2269-2276, 24th International Conference on Pattern Recognition, Beijing, China, 20/08/18. DOI: 10.1109/ICPR.2018.8545422

Hu, C, Li, D, Song, Y-Z, Xiang, T & Hospedales, T 2018, Sketch-a-Classifier: Sketch-based Photo Classifier Generation. in Computer Vision and Pattern Recognition 2018. IEEE, Computer Vision and Pattern Recognition 2018, Salt Lake City, United States, 18/06/18.

Song, J, Pang, K, Song, Y-Z, Xiang, T & Hospedales, T 2018, Learning to Sketch with Shortcut Cycle Consistency. in Computer Vision and Pattern Recognition 2018. IEEE, Computer Vision and Pattern Recognition 2018, Salt Lake City, United States, 18/06/18.

Xu, P, Huang, Y, Yuan, T, Pang, K, Song, Y-Z, Xiang, T, Hospedales, T, Ma, Z & Guo, J 2018, SketchMate: Deep Hashing for Million-Scale Human Sketch Retrieval. in Computer Vision and Pattern Recognition 2018. IEEE, Computer Vision and Pattern Recognition 2018, Salt Lake City, United States, 18/06/18.

Liu, F, Xiang, T, Hospedales, T, Yang, W & Sun, C 2018, iVQA: Inverse Visual Question Answering. in Computer Vision and Pattern Recognition 2018. IEEE, Computer Vision and Pattern Recognition 2018, Salt Lake City, United States, 18/06/18.

Chang, X, Hospedales, T & Xiang, T 2018, Multi-Level Factorisation Net for Person Re-Identification. in Computer Vision and Pattern Recognition 2018. IEEE, Computer Vision and Pattern Recognition 2018, Salt Lake City, United States, 18/06/18.

Chang, X, Xiang, T & Hospedales, T 2018, Scalable and Effective Deep CCA via Soft Decorrelation. in Computer Vision and Pattern Recognition 2018. IEEE, Computer Vision and Pattern Recognition 2018, Salt Lake City, United States, 18/06/18.

Zhang, Y, Xiang, T, Hospedales, T & Lu, H 2018, Deep Mutual Learning. in Computer Vision and Pattern Recognition 2018. IEEE, Computer Vision and Pattern Recognition 2018, Salt Lake City, United States, 18/06/18.

Muhammad, UR, Yang, Y, Song, Y-Z, Xiang, T & Hospedales, T 2018, Learning Deep Sketch Abstraction. in Computer Vision and Pattern Recognition 2018. Computer Vision and Pattern Recognition 2018, Salt Lake City, United States, 18/06/18.

Rauch, C, Hospedales, T, Shotton, J & Fallon, M 2018, Visual Articulated Tracking in the Presence of Occlusions. in International Conference on Robotics and Automation (ICRA 2018). IEEE, Brisbane, QLD, Australia, pp. 643-650, 2018 IEEE International Conference on Robotics and Automation, Brisbane, Australia, 21/05/18. DOI: 10.1109/ICRA.2018.8462873

Hu, G, Hu, Y, Yang, K, Yu, Z, Sung, F, Zhang, Z, Xie, F, Liu, J, Robertson, N, Hospedales, T & Miemie, Q 2018, Deep Stock Representation Learning: From Candlestick Charts to Investment Decisions. in 2018 IEEE International Conference on Acoustics, Speech and Signal Processing. IEEE, Calgary, AB, Canada, pp. 2706-2710, 2018 IEEE International Conference on Acoustics, Speech and Signal Processing, Calgary, Canada, 15/04/18. DOI: 10.1109/ICASSP.2018.8462215

Sung, F, Yang, Y, Zhang, L, Xiang, T, Torr, PHS & Hospedales, T 2018, Learning to Compare: Relation Network for Few-Shot Learning. in Computer Vision and Pattern Recognition 2018. Computer Vision and Pattern Recognition 2018, Salt Lake City, United States, 18/06/18.

Zhang, L, Sung, F, Liu, F, Xiang, T, Gong, S, Yang, Y & Hospedales, T 2017, Actor-Critic Sequence Training for Image Captioning. in Visually-Grounded Interaction and Language (ViGIL at NIPS 2017). Visually-Grounded Interaction and Language (ViGIL), Long Beach, United States, 8/12/17.

Yang, Y & Hospedales, T 2015, A Unified Perspective on Multi-Domain and Multi-Task Learning. in 3rd International Conference on Learning Representations (ICLR). 3rd International Conference on Learning Representations, San Diego, United States, 7/05/15.

Yang, Y & Hospedales, T 2015, Zero-Shot Domain Adaptation via Kernel Regression on the Grassmannian. in 1st International Workshop on Differential Geometry in Computer Vision (Diff-CV). 1st International Workshop on DIFFerential Geometry in Computer Vision for Analysis of Shapes, Images and Trajectories (DIFF-CV), Swansea, United Kingdom, 10/09/15. DOI: 10.5244/C.29.DIFFCV.1

Yang, Y & Hospedales, T 2017, Trace Norm Regularised Deep Multi-Task Learning. in 5th International Conference on Learning Representations Workshop. 5th International Conference on Learning Representations, Toulon, France, 24/04/17.

Yang, Y & Hospedales, TM 2017, Unifying multi-domain multitask learning: Tensor and neural network perspectives. in Advances in Computer Vision and Pattern Recognition. Advances in Computer Vision and Pattern Recognition, no. 9783319583464, Springer London, pp. 291-309. DOI: 10.1007/978-3-319-58347-1_16

Li, D, Yang, Y, Song, Y-Z & Hospedales, T 2018, Learning to Generalize: Meta-Learning for Domain Generalization. in AAAI Conference on Artificial Intelligence (AAAI 2018). Thirty-Second AAAI Conference on Artificial Intelligence, New Orleans, United States, 2/02/18.

Li, K, Pang, K, Song, YZ, Hospedales, TM, Xiang, T & Zhang, H 2017, 'Synergistic Instance-Level Subspace Alignment for Fine-Grained Sketch-Based Image Retrieval' IEEE Transactions on Image Processing, vol. 26, no. 12, pp. 5908 - 5921. DOI: 10.1109/TIP.2017.2745106

Hu, G, Peng, X, Yang, Y, Hospedales, T & Verbeek, J 2017, 'Frankenstein: Learning Deep Face Representations using Small Data' IEEE Transactions on Image Processing. DOI: 10.1109/TIP.2017.2756450

Hu, G, Yang, H, Yuan, Y, Zhang, Z, Lu, Z, Mukherjee, SS, Hospedales, T, Robertson, NM & Yang, Y 2017, Attribute-Enhanced Face Recognition with Neural Tensor Fusion Networks. in The International Conference on Computer Vision (ICCV 2017). IEEE, pp. 3764-3773, 2017 IEEE International Conference on Computer Vision, Venice, Italy, 22/10/17. DOI: 10.1109/ICCV.2017.404

Li, D, Yang, Y, Song, Y-Z & Hospedales, T 2017, Deeper, Broader and Artier Domain Generalization. in The International Conference on Computer Vision (ICCV 2017). IEEE, pp. 5543-5551, 2017 IEEE International Conference on Computer Vision, Venice, Italy, 22/10/17. DOI: 10.1109/ICCV.2017.591

Song, J, Yu, Q, Song, Y-Z, Xiang, T & Hospedales, T 2017, Deep Spatial-Semantic Attention for Fine-Grained Sketch-Based Image Retrieval. in The International Conference on Computer Vision (ICCV 2017). IEEE, pp. 5552-5561, International Conference on Computer Vision Workshop 2017, Venice, Italy, 22/10/17. DOI: 10.1109/ICCV.2017.592

Pang, K, Song, Y-Z, Xiang, T & Hospedales, T 2017, Cross-domain Generative Learning for Fine-Grained Sketch-Based Image Retrieval. in The British Machine Vision Conference (BMVC 2017). The 28th British Machine Vision Conference , London, United Kingdom, 4/09/17.

Song, J, Song, Y-Z, Xiang, T & Hospedales, T 2017, Fine-Grained Image Retrieval: the Text/Sketch Input Dilemma. in The British Machine Vision Conference (BMVC 2017). The 28th British Machine Vision Conference , London, United Kingdom, 4/09/17.

Hu, C, Li, D, Song, Y-Z & Hospedales, TM 2017, Now You See Me: Deep Face Hallucination for Unviewed Sketches. in The British Machine Vision Conference (BMVC 2017). The 28th British Machine Vision Conference , London, United Kingdom, 4/09/17.

Alameda-Pineda, X, Hospedales, TM, Ricci, E, Sebe, N & Wang, X 2016, Emerging Topics in Learning from Noisy and Missing Data. in Proceedings of the 2016 ACM on Multimedia Conference. MM '16, ACM, New York, NY, USA, pp. 1469-1470, ACM MULTIMEDIA CONFERENCE 2016, Amsterdam, Netherlands, 15/10/16. DOI: 10.1145/2964284.2986910

Dong, M, Pang, K, Wu, Y, Xue, J-H, Hospedales, T & Ogasawara, T 2018, Transferring CNNs to Multi-instance Multi-label Classification on Small Datasets. in 2017 IEEE International Conference on Image Processing (ICIP). pp. 1332-1336, 2017 IEEE International Conference on Image Processing, Beijing, China, 17/09/17. DOI: 10.1109/ICIP.2017.8296498

Layne, R, Hannuna, S, Camplani, M, Hall, J, Hospedales, T, Xiang, T, Mirmehdi, M & Damen, D 2017, A Dataset for Persistent Multi-Target Multi-Camera Tracking in RGB-D. in 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). IEEE, pp. 1462-1470, 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops, Honolulu, United States, 21/07/17. DOI: 10.1109/CVPRW.2017.189

Zhao, C, Hospedales, T, Stulp, F & Sigaud, O 2017, Tensor Based Knowledge Transfer Across Skill Categories for Robot Control. in Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17). IJCAI Inc, pp. 3462-3468, 26th International Joint Conference on Artificial Intelligence, Melbourne, Australia, 19/08/17. DOI: 10.24963/ijcai.2017/484

Fu, Y, Hospedales, TM, Xiang, T & Gong, S 2012, Attribute Learning for Understanding Unstructured Social Activity. in Computer Vision - ECCV 2012 - 12th European Conference on Computer Vision, Florence, Italy, October 7-13, 2012, Proceedings, Part IV. Lecture Notes in Computer Science (LNCS), vol. 7575, Springer Berlin Heidelberg, pp. 530-543. DOI: 10.1007/978-3-642-33765-9_38

Hospedales, TM, Gong, S & Xiang, T 2012, A Unifying Theory of Active Discovery and Learning. in Computer Vision - ECCV 2012 - 12th European Conference on Computer Vision, Florence, Italy, October 7-13, 2012, Proceedings, Part V. Lecture Notes in Computer Science (LNCS), vol. 7576, Springer Berlin Heidelberg, pp. 453-466. DOI: 10.1007/978-3-642-33715-4_33

Layne, R, Hospedales, TM & Gong, S 2012, Towards Person Identification and Re-identification with Attributes. in Computer Vision - ECCV 2012. Workshops and Demonstrations - Florence, Italy, October 7-13, 2012, Proceedings, Part I. Lecture Notes in Computer Science (LNCS), vol. 7583, Springer Berlin Heidelberg, pp. 402-412. DOI: 10.1007/978-3-642-33863-2_40

Loy, CC, Hospedales, TM, Xiang, T & Gong, S 2012, Stream-based joint exploration-exploitation active learning. in 2012 IEEE Conference on Computer Vision and Pattern Recognition. IEEE, pp. 1560-1567. DOI: 10.1109/CVPR.2012.6247847

Layne, R, Hospedales, TM & Gong, S 2012, Person Re-identification by Attributes. in British Machine Vision Conference, BMVC 2012, Surrey, UK, September 3-7, 2012. BMVA Press, pp. 1-11. DOI: 10.5244/C.26.24

Hospedales, TM, Gong, S & Xiang, T 2012, 'Video Behaviour Mining Using a Dynamic Topic Model' International Journal of Computer Vision, vol. 98, no. 3, pp. 303-323. DOI: 10.1007/s11263-011-0510-7

Xu, X, Gong, S & Hospedales, T 2013, Cross-domain Traffic Scene Understanding by Motion Model Transfer. in Proceedings of the 4th ACM/IEEE International Workshop on Analysis and Retrieval of Tracked Events and Motion in Imagery Stream. ARTEMIS '13, ACM, New York, NY, USA, pp. 77-86. DOI: 10.1145/2510650.2510657

Layne, R, Hospedales, TM & Gong, S 2013, Domain Transfer for Person Re-identification. in Proceedings of the 4th ACM/IEEE International Workshop on Analysis and Retrieval of Tracked Events and Motion in Imagery Stream. ARTEMIS '13, ACM, New York, NY, USA, pp. 25-32. DOI: 10.1145/2510650.2510658

Shi, Z, Hospedales, TM & Xiang, T 2013, Bayesian Joint Topic Modelling for Weakly Supervised Object Localisation. in 2013 IEEE International Conference on Computer Vision. IEEE, pp. 2984-2991. DOI: 10.1109/ICCV.2013.371

Hospedales, TM, Gong, S & Xiang, T 2011, 'Finding Rare Classes: Active Learning with Generative and Discriminative Models' IEEE Transactions on Knowledge and Data Engineering, vol. 25, no. 2, pp. 374-386. DOI: 10.1109/TKDE.2011.231

Layne, R, Hospedales, TM & Gong, S 2014, Attributes-Based Re-identification. in Person Re-Identification. Advances in Computer Vision and Pattern Recognition, Springer London, pp. 93-117. DOI: 10.1007/978-1-4471-6296-4_5

Gong, S, Cristani, M, Loy, CC & Hospedales, TM 2014, The Re-identification Challenge. in Person Re-Identification. Advances in Computer Vision and Pattern Recognition, Springer London, pp. 1-20. DOI: 10.1007/978-1-4471-6296-4_1

Fu, Y, Hospedales, TM, Xiang, T, Fu, Z-Y & Gong, S 2014, Transductive Multi-view Embedding for Zero-Shot Recognition and Annotation. in Computer Vision - ECCV 2014 - 13th European Conference, Zurich, Switzerland, September 6-12, 2014, Proceedings, Part II. Lecture Notes in Computer Science (LNCS), vol. 8690, Springer, Cham, pp. 584-599. DOI: 10.1007/978-3-319-10605-2_38

Fu, Y, Hospedales, TM, Xiang, T, Gong, S & Yao, Y 2014, Interestingness Prediction by Robust Learning to Rank. in Computer Vision - ECCV 2014 - 13th European Conference, Zurich, Switzerland, September 6-12, 2014, Proceedings, Part II. Lecture Notes in Computer Science (LNCS), vol. 8690, Springer, Cham, pp. 488-503. DOI: 10.1007/978-3-319-10605-2_32

Shi, Z, Yang, Y, Hospedales, TM & Xiang, T 2014, Weakly Supervised Learning of Objects, Attributes and Their Associations. in Computer Vision - ECCV 2014 - 13th European Conference, Zurich, Switzerland, September 6-12, 2014, Proceedings, Part II. Lecture Notes in Computer Science (LNCS), vol. 8690, Springer, Cham, pp. 472-487. DOI: 10.1007/978-3-319-10605-2_31

Layne, R, Hospedales, TM & Gong, S 2014, Investigating Open-World Person Re-identification Using a Drone. in Computer Vision - ECCV 2014 Workshops - Zurich, Switzerland, September 6-7 and 12, 2014, Proceedings, Part III. Lecture Notes in Computer Science (LNCS), vol. 8927, Springer International Publishing, pp. 225-240. DOI: 10.1007/978-3-319-16199-0_16

Li, Y, Hospedales, TM, Song, Y-Z & Gong, S 2014, Intra-category sketch-based image retrieval by matching deformable part models. in British Machine Vision Conference, BMVC 2014, Nottingham, UK, September 1-5, 2014. BMVA Press. DOI: 10.5244/C.28.115

Layne, R, Hospedales, TM & Gong, S 2014, Re-id: Hunting Attributes in the Wild. in British Machine Vision Conference, BMVC 2014, Nottingham, UK, September 1-5, 2014. BMVA Press. DOI: 10.5244/C.28.1

Fu, Y, Yang, Y, Hospedales, TM, Xiang, T & Gong, S 2014, Transductive Multi-label Zero-shot Learning. in British Machine Vision Conference, BMVC 2014, Nottingham, UK, September 1-5, 2014. BMVA Press. DOI: 10.5244/C.28.7

Cancela, B, Hospedales, TM & Gong, S 2014, Open-world Person Re-Identification by Multi-Label Assignment Inference. in British Machine Vision Conference, BMVC 2014, Nottingham, UK, September 1-5, 2014. BMVA Press. DOI: 10.5244/C.28.98

Ouyang, S, Hospedales, TM, Song, Y-Z & Li, X 2014, Cross-Modal Face Matching: Beyond Viewed Sketches. in Computer Vision - ACCV 2014 - 12th Asian Conference on Computer Vision, Singapore, Singapore, November 1-5, 2014, Revised Selected Papers, Part II. Lecture Notes in Computer Science (LNCS), vol. 9004, Springer International Publishing, pp. 210-225. DOI: 10.1007/978-3-319-16808-1_15

Fu, Y, Hospedales, TM, Xiang, T & Gong, S 2014, 'Learning Multimodal Latent Attributes' IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 36, no. 2, pp. 303-316. DOI: 10.1109/TPAMI.2013.128

Xu, X, Hospedales, T & Gong, S 2015, Semantic embedding space for zero-shot action recognition. in 2015 IEEE International Conference on Image Processing (ICIP). IEEE, pp. 63-67. DOI: 10.1109/ICIP.2015.7350760

Hu, G, Yang, Y, Yi, D, Kittler, J, Christmas, W, Li, SZ & Hospedales, T 2015, When Face Recognition Meets with Deep Learning: An Evaluation of Convolutional Neural Networks for Face Recognition. in 2015 IEEE International Conference on Computer Vision Workshop (ICCVW). IEEE, pp. 384-392. DOI: 10.1109/ICCVW.2015.58

Shi, Z, Hospedales, TM & Xiang, T 2015, Transferring a semantic representation for person re-identification and search. in 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, pp. 4184-4193. DOI: 10.1109/CVPR.2015.7299046

Qi, Y, Song, YZ, Xiang, T, Zhang, H, Hospedales, T, Li, Y & Guo, J 2015, Making better use of edges via perceptual grouping. in 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, pp. 1856-1865. DOI: 10.1109/CVPR.2015.7298795

Yu, Q, Yang, Y, Song, Y-Z, Xiang, T & Hospedales, T 2015, Sketch-a-Net that Beats Humans. in MWJ Xianghua Xie & GKL Tam (eds), Proceedings of the British Machine Vision Conference (BMVC)., 7, BMVA Press, pp. 1-12. DOI: 10.5244/C.29.7

Fu, Y, Hospedales, TM, Xiang, T & Gong, S 2015, 'Transductive Multi-View Zero-Shot Learning' IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 37, no. 11, pp. 2332-2345. DOI: 10.1109/TPAMI.2015.2408354

Shi, Z, Hospedales, TM & Xiang, T 2015, 'Bayesian Joint Modelling for Object Localisation in Weakly Labelled Images' IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 37, no. 10, pp. 1959-1972. DOI: 10.1109/TPAMI.2015.2392769

Li, Y, Hospedales, TM, Song, Y-Z & Gong, S 2015, 'Free-hand sketch recognition by multi-kernel feature learning' Computer Vision and Image Understanding, vol. 137, pp. 1-11. DOI: 10.1016/j.cviu.2015.02.003

Hospedales, TM, Li, J, Gong, S & Xiang, T 2011, 'Identifying Rare and Subtle Behaviors: A Weakly Supervised Joint Topic Model' IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 33, no. 12, pp. 2451-2464. DOI: 10.1109/TPAMI.2011.81

Hospedales, TM, Gong, S & Xiang, T 2011, Learning Tags from Unsegmented Videos of Multiple Human Actions. in 2011 IEEE 11th International Conference on Data Mining. IEEE, 978-1-4577-2075-8, pp. 251-259. DOI: 10.1109/ICDM.2011.90

Hospedales, TM, Gong, S & Xiang, T 2011, Finding Rare Classes: Adapting Generative and Discriminative Models in Active Learning. in Advances in Knowledge Discovery and Data Mining: 15th Pacific-Asia Conference, PAKDD 2011, Shenzhen, China, May 24-27, 2011, Proceedings, Part II. Lecture Notes in Computer Science (LNCS), vol. 6635, Springer Berlin Heidelberg, pp. 296-308. DOI: 10.1007/978-3-642-20847-8_25

Hospedales, T, Gong, S & Xiang, T 2009, A Markov Clustering Topic Model for mining behaviour in video. in 2009 IEEE 12th International Conference on Computer Vision. IEEE, pp. 1165-1172. DOI: 10.1109/ICCV.2009.5459342

Zelniker, EE, Hospedales, TM, Gong, S & Xiang, T 2009, A Unified Bayesian Framework for Adaptive Visual Tracking. in Proceedings of the British Machine Vision Conference., 18, BMVA Press, pp. 1-11. DOI: 10.5244/C.23.18

Hospedales, TM & Williams, O 2008, An Adaptive Machine Director. in Proceedings of the British Machine Vision Conference 2008, Leeds, September 2008. BMVA Press, pp. 1-10. DOI: 10.5244/C.22.118

Li, J, Hospedales, TM, Gong, S & Xiang, T 2010, Learning Rare Behaviours. in Computer Vision - ACCV 2010 - 10th Asian Conference on Computer Vision, Queenstown, New Zealand, November 8-12, 2010, Revised Selected Papers, Part II. Lecture Notes in Computer Science (LNCS), vol. 6493 , Springer Berlin Heidelberg, pp. 293-307. DOI: 10.1007/978-3-642-19309-5_23

Ouyang, S, Hospedales, T, Song, Y-Z, Li, X, Loy, CC & Wang, X 2016, 'A survey on heterogeneous face recognition: Sketch, infra-red, 3D and low-resolution' Image and vision computing, vol. 56, pp. 28-48. DOI: 10.1016/j.imavis.2016.09.001

Liu, F, Xiang, T, Hospedales, T, Yang, W & Sun, C 2017, Semantic Regularisation for Recurrent Image Annotation. in Computer Vision and Pattern Recognition (CVPR 2017). Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. Honolulu 2017., Honolulu, United States, 21/07/17. DOI: 10.1109/CVPR.2017.443

Yang, Y & Hospedales, T 2017, Deep Multi-task Representation Learning: A Tensor Factorisation Approach. in International Conference on Learning Representations (ICLR 2017). 5th International Conference on Learning Representations, Toulon, France, 24/04/17.

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Ghosh, S, Burns, C, Clark, D, Gorgolewski, KJ, Halchenko, Y, Madison, C, Tungaraza, R & Millman, J 2010, 'Nipype: Opensource platform for unified and replicable interaction with existing neuroimaging tools' 16th Annual Meeting of the Organization for Human Brain Mapping, Barcelona, Spain, 6/06/10 - 10/06/10, .

Buchanan, CR, Pernet, C, Gorgolewski, KJ, Storkey, A & Bastin, M 2013, 'The test-retest reliability of structural brain networks obtained from diffusion MRI' 19th Annual Meeting of the Organization for Human Brain Mapping, Seattle, Washington, United States, 16/06/13 - 20/06/13, .

Gorgolewski, KJ, Storkey, A, Bastin, M & Pernet, C 2012, Reliability of single subject fMRI in the context of presurgical planning. in 18th Annual Meeting of the Organization for Human Brain Mapping.

Poline, J-B, Breeze, JL, Ghosh, SS, Gorgolewski, KJ, Halchenko, YO, Hanke, M, Helmer, KG, Marcus, DS, Poldrack, RA, Schwartz, Y, Ashburner, J & Kennedy, DN 2012, 'Data sharing in neuroimaging research' Frontiers in Neuroinformatics, vol. 6, no. 9. DOI: 10.3389/fninf.2012.00009

Buchanan, C, Gorgolewski, KJ, Pernet, C, Storkey, A & Bastin, M 2012, 'Quantifying the intra- and inter-subject variability of whole-brain structural networks from diffusion MRI' ISMRM 20th Annual Meeting & Exhibition, Melbourne, Australia, 5/05/12 - 11/05/12, .

Buchanan, CR, Pernet, CR, Gorgolewski, KJ, Storkey, AJ & Bastin, ME 2014, 'Test-retest reliability of structural brain networks from diffusion MRI' NeuroImage, vol. 86, pp. 231-243. DOI: 10.1016/j.neuroimage.2013.09.054

Gorgolewski, KJ, Storkey, AJ, Bastin, ME & Pernet, CR 2012, 'Adaptive thresholding for reliable topological inference in single subject fMRI analysis' Frontiers in Human Neuroscience, vol. 6, 245. DOI: 10.3389/fnhum.2012.00245

Gorgolewski, KJ, Storkey, A, Bastin, ME, Whittle, IR, Wardlaw, JM & Pernet, CR 2013, 'A test-retest fMRI dataset for motor, language and spatial attention functions' GigaScience, vol. 2, no. 1, 6. DOI: 10.1186/2047-217X-2-6

Gorgolewski, KJ, Storkey, AJ, Bastin, ME, Whittle, I & Pernet, C 2013, 'Single subject fMRI test-retest reliability metrics and confounding factors' NeuroImage, vol. 69, pp. 231-43. DOI: 10.1016/j.neuroimage.2012.10.085

Glatz, A, Buchanan, C, Valdes Hernandez, M, Bastin, M & Wardlaw, J 2012, 'Intuitive and efficient deployment of neuroimaging pipelines in clinical research with BRICpipe: Clinical neuroscience' 5th World INCF Neuroinformatics Congress, Munich, Germany, Germany, 10/09/12 - 12/09/12, .

Buchanan, C 2012, 'Whole-brain structural networks from diffusion MRI' 2nd UK Neuroinformatics Node Congress, Edinburgh, United Kingdom, 26/03/12 - 28/03/12, .

Jelitai, M, Puggioni, P, Ishikawa, T, Rinaldi, A & Duguid, I 2016, 'Dendritic excitation-inhibition balance shapes cerebellar output during motor behaviour' Nature Communications, vol. 7, 13722. DOI: 10.1038/ncomms13722

Schiemann, J, Puggioni, P, Pelko, M, Domanski, A, Van Rossum, M & Duguid, I 2015, 'Cellular mechanisms underlying behavioral state-dependent bidirectional modulation of motor cortex output' Cell Reports, vol. 11, no. 8, pp. 1319–1330. DOI: 10.1016/j.celrep.2015.04.042

Puggioni, P, Pelko, M, Van Rossum, M & Duguid, I 2013, 'Behavioral state differentially regulates input sensitivity and firing rates of motor cortex pyramidal neurons' BMC Neuroscience, vol. 14. DOI: 10.1186/1471-2202-14-S1-P114

Pelko, M, Puggioni, P, Van Rossum, M & Bouscein, C 2012, 'Determining synaptic input properties from intra-cellular recordings in vivo'.

Puggioni, P, Pelko, M, Van Rossum, M & Duguid, I 2013, 'Integrative properties of motor cortex pyramidal cells during quiet wakefulness and movement' Computational and Systems Neuroscience (Cosyne) 2013, Salt Lake City, Utah, United States, 28/02/13 - 5/03/13, pp. 190.

Puggioni, P, Van Rossum, M & Duguid, I 2012, 'Layer Specific Sub- And Suprathreshold Coding Of Voluntary Movements In The Motor Cortex Of Awake Mice' 8th Fens Forum of Neuroscience, Barcelona, Spain, 14/07/12 - 18/07/12, pp. 155.08.

Puggioni, P, Pelko, M, Van Rossum, M & Duguid, I 2012, 'Layer specific sub- and suprathreshold coding of voluntary movements in the motor cortex of awake mice' Society for Neuroscience Annual Meeting 2012, New Orleans, 13/10/12 - 17/10/12, .

Suslak, TJ & Jarman, AP 2015, 'Stretching the imagination beyond muscle spindles - stretch-sensitive mechanisms in arthropods' Journal of Anatomy. DOI: 10.1111/joa.12329

Suslak, T, Watson, S, Thompson, KJ, Shenton, FC, Bewick, GS, Armstrong, JD & Jarman, AP 2015, 'Piezo is essential for amiloride-sensitive stretch-activated mechanotransduction in larval Drosophila dorsal bipolar dendritic sensory neurons' PLoS One, vol. 10, no. 7, e0130969.

Suslak, T, Armstrong, DJ & Jarman, A 2011, 'A general mathematical model of transduction events in mechano-sensory stretch receptors' 2nd Scottish Drosophila Research Conference, Dundee, United Kingdom, 9/12/11, .

Suslak, T, McKay-Fletcher, JA, Armstrong, D, Jarman, A & Bewick, G 2013, 'Modelling mechanotransduction in primary sensory endings' Neuroinformatics 2013 6th INCF Congress, Stockholm, Sweden, 27/08/13 - 29/08/13, .

Suslak, T, Bewick, G, Armstrong, D & Jarman, A 2013, 'A model of mechanotransduction in Drosophila non-ciliated, primary endings' Physiology 2013 (IUPS), Birmingham, United Kingdom, 21/07/13 - 26/07/13, .

Suslak, T, McKay-Fletcher, JA, Bewick, G, Armstrong, D & Jarman, A 2013, 'A model of mechanotransduction in Drosophila non-ciliated, primary endings' Neuroscience Day 2013, Edinburgh, United Kingdom, 20/03/13 - 20/03/13, .

Suslak, T, Jarman, A & Armstrong, D 2011, 'A mathematical model of electrical transduction events in crayfish stretch receptors'.

Armstrong, JD, Jarman, AP & Suslak, T 2011, 'A general mathematical model of transduction events in mechano-sensory stretch receptors' Network: Computation in Neural Systems, vol. 22, no. 1-4, pp. 133-42. DOI: 10.3109/0954898X.2011.638967

Suslak, T, Bewick, G, Armstrong, D & Jarman, A 2012, 'A general mathematical model of transduction events in mechanosensory stretch receptors' Physiology 2012, Edinburgh, United Kingdom, 2/07/12 - 5/07/12, .

Stevens, J-L, Chemla, S, Benvenuti, G, Chavane, F & Bednar, J 2014, 'A model relating temporal processing across spatial and temporal scales using electrophysiological and optical imaging data in primate V1' 44th Society for Neuroscience Annual Meeting, Washington, DC, United States, 15/11/14 - 19/11/14, .

Stevens, J-L, Elver, M & Bednar, JA 2013, 'An automated and reproducible workflow for running and analyzing neural simulations using Lancet and IPython Notebook' Frontiers in Neuroinformatics, vol. 7.

Rudiger, P, Stevens, J-L, Talluri, B & Bednar, JA 2014, 'Relationship between natural image statistics and lateral connectivity in the primary visual cortex' Computational and Systems Neuroscience (Cosyne) 2014, Salt Lake City, United States, 27/02/14 - 2/03/14, pp. 148-149.

Stevens, J-L & Bednar, J 2012, 'A temporal model of neural activity and VSD response in V1' 21st Annual Computational Neurscience Meeting: CNS 2012, Decatur, United States, 21/07/12 - 26/07/12, .

Stevens, J-L, Elver, M & Bednar, J 2013, 'An automated simulator-independent workflow for reproducible simulation and analysis using Lancet and IPython Notebook' 22nd Annual Computational Neuroscience Meeting: CNS 2013, Paris, France, 13/07/13 - 18/07/13, . DOI: 10.1186/1471-2202-14-S1-P22

Rudiger, P, Stevens, J-L & Bednar, J 2012, 'A spatio-temporally calibrated model of feature map development and neuronal activity in primate V1' Society for Neuroscience Annual Meeting 2012, New Orleans, 13/10/12 - 17/10/12, .

Rudiger, P & Bednar, J 2014, 'Relating the diversity of interneuronal subtypes to their functional roles in development, homeostasis and sensory processing' 44th Society for Neuroscience Annual Meeting, Washington, DC, United States, 15/11/14 - 19/11/14, .

Rudiger, P & Bednar, JA 2013, 'Unifying anatomical, psychophysical, and developmental circuit models of primary visual cortex' Society for Neuroscience Annual Meeting 2013, San Diego, United States, 9/11/13 - 13/11/13, .

Van Rossum, M & Pelko, M 2015, 'Stability of Neuronal Networks with Homeostatic Regulation' PLoS Computational Biology. DOI: 10.1371/journal.pcbi.1004357

Pelko, M & Van Rossum, M 2012, 'Membrane Voltage Dynamics in Active vs. Passive Mice: The Role of Input Correlations' 8th Fens Forum of Neuroscience, Barcelona, Spain, 14/07/12 - 18/07/12, .

Pelko, M & Van Rossum, M 2011, 'The effects of input integration structure on the spiking responses in the Hodgin-Huxley models' Mathematical Neuroscience 2011, Edinburgh, United Kingdom, 11/04/11 - 13/04/11, .

Gekas, N, Seitz, AR & Seriés, P 2015, 'Expectations developed over multiple timescales facilitate visual search performance' Journal of Vision, vol. 15, no. 9, 10. DOI: 10.1167/15.9.10

Seitz, A, Seriès, P & Gekas, N 2012, 'Investigating the specificity of experimentally induced expectations in motion perception' Journal of Vision, vol. 12, no. 9, pp. 1137. DOI: 10.1167/12.9.1137

Shipston-Sharman, O, Solanka, L & Nolan, M 2016, 'Continuous attractor network models of grid cell firing based on excitatory-inhibitory interactions' Journal of Physiology. DOI: 10.1113/JP270630

Solanka, L, van Rossum, MCW & Nolan, MF 2015, 'Noise promotes independent control of gamma oscillations and grid firing within recurrent attractor networks' eLIFE, vol. 4. DOI: 10.7554/eLife.06444

Solanka, L, Pastoll, H, Nolan, M & van Rossum, MCW 2012, 'Co-existence of theta-nested gamma oscillations and grid firing fields in an attractor network model' Physiology 2012, Edinburgh, United Kingdom, 2/07/12 - 5/07/12, .

Solanka, L, Van Rossum, M & Nolan, M 2011, 'Stability of two dimensional spiking attractor network models of grid cells' UK Neuroinformatics: From Computational Models to Engineering and Cognition, Manchester, United Kingdom, 29/11/11 - 30/11/11, .

Solanka, L, Pastoll, H, Nolan, MF & Van Rossum, MCW 2012, 'Multiplexing of theta-nested gamma oscillations and grid firing fields in an attractor network model of layer II of the medial entorhinal cortex' Frontiers in Computational Neuroscience, no. 252. DOI: 10.3389/conf.fncom.2012.55.00252

Solanka, L, Pastoll, H, Nolan, M & Van Rossum, MCW 2013, 'Co-existence of theta-nested gamma oscillations and grid firing fields in an attractor network model' Society for Neuroscience Annual Meeting 2013, San Diego, United States, 9/11/13 - 13/11/13, .

Pastoll, H, Solanka, L, van Rossum, MCW & Nolan, MF 2013, 'Feedback Inhibition Enables Theta-Nested Gamma Oscillations and Grid Firing Fields' Neuron, vol. 77, no. 1, pp. 141-154. DOI: 10.1016/j.neuron.2012.11.032

Acerbi, L, Vijayakumar, S, Wolpert, DM & Buckingham, G (ed.) 2017, 'Target Uncertainty Mediates Sensorimotor Error Correction' PLoS One, vol. 12, no. 1, e0170466, pp. 1-21. DOI: 10.1371/journal.pone.0170466

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Acerbi, L, Ma, WJ & Vijayakumar, S 2014, A Framework for Testing Identifiability of Bayesian Models of Perception. in Z Ghahramani, M Welling, C Cortes, ND Lawrence & KQ Weinberger (eds), Advances in Neural Information Processing Systems 27. Curran Associates Inc, pp. 1026-1034.

Acerbi, L, Vijayakumar, S & Wolpert, DM 2014, 'On the Origins of Suboptimality in Human Probabilistic Inference' PLoS Computational Biology, vol. 10, no. 6, 1003661. DOI: 10.1371/journal.pcbi.1003661

Acerbi, L, Marius 't Hart, B, Behbahani, FMP & Peters, MAK 2013, 'Optimality under fire: Dissociating learning from Bayesian integration'.

Acerbi, L, Wolpert, D & Vijayakumar, S 2014, 'Probing the sources of suboptimality in human Bayesian inference' Computational and Systems Neuroscience (Cosyne) 2014, Salt Lake City, United States, 27/02/14 - 2/03/14, .

Acerbi, L, Wolpert, D & Vijayakumar, S 2012, 'Internal representations of temporal statistics and feedback in sensorimotor interval timing' 9th Annual Annual Computational and Systems Neurscience Meeting (COSYNE 2012), Salt Lake City, United States, 23/02/12 - 26/02/12, .

Acerbi, L, Wolpert, D & Vijayakumar, S 2012, 'Internal Representations of Temporal Statistics and Feedback Calibrate Motor-Sensory Interval Timing' PLoS Computational Biology, vol. 8, no. 11, e1002771. DOI: 10.1371/journal.pcbi.1002771

Acerbi, L & Vijayakumar, S 2011, 'Bayesian causal inference drives temporal sensorimotor recalibration'.

Costa, RP, Froemke, RC, Sjöström, PJ & Van Rossum, MCW 2015, 'Unified pre- and postsynaptic long-term plasticity enables reliable and flexible learning' eLIFE, vol. 4. DOI: 10.7554/eLife.09457

Costa, RP, Sjostrom, PJ & van Rossum, MCW 2013, 'Probabilistic Inference Reveals Synapse-specific Synaptic Dynamics in Neocortical Microcircuits' Computational and Systems Neuroscience (Cosyne) 2013, Salt Lake City, Utah, United States, 28/02/13 - 5/03/13, .

Costa, RP, Buchanan, KA, Elgar, D, Blackman, AV, Oyrer, J, Van Rossum, M & Sjöström, PJ 2012, 'Presynaptic NMDA receptors differentially regulate release probability at neocortical excitatory synapses' Society for Neuroscience Annual Meeting 2012, New Orleans, 13/10/12 - 17/10/12, .

Costa, RP, Sjöström, PJ & Van Rossum, M 2013, 'Probabilistic inference of synaptic dynamics in neocortical microcircuits' 22nd Annual Computational Neuroscience Meeting: CNS 2013, Paris, France, 13/07/13 - 18/07/13, .

Costa, RP, Van Rossum, M & Sjöström, PJ 2011, 'The Impact of Synaptic Dynamics on the Structure of Plastic Networks' Workshop on Learning and Plasticity, Marseille, France, France, 7/11/11 - 11/11/11, .

Direito, B, Costa, RP, Feldwisch-Drentrup, H, Valderrama, M, Nikolopoulos, S, Schelter, B, Jachan, M, Teixeira, CA, Aires, L, Timmer, J, Le Van Quyen, M & Dourado, A 2011, EPILAB: A MATLAB platform for multi-feature and multi-algorithm seizure prediction. in I Osorio, HP Zaveri, MG Frei & S Arthurs (eds), Epilepsy: The intersection of neurosciences, mathematics and engineering. 1 edn, Taylor & Francis, pp. 417.

Costa, RP & Sjöström, PJ 2011, 'One cell to rule them all, and in the dendrites bind them' Frontiers in synaptic neuroscience, vol. 3, no. 5. DOI: 10.3389/fnsyn.2011.00005

Teixeira, CA, Direito, B, Costa, RP, Valderrama, M, Feldwisch-Drentrup, H, Nikolopoulos, S, Le Van Quyen, M, Schelter, B & Dourado, A 2010, A computational environment for long-term multi-feature and multi-algorithm seizure prediction. in Engineering in Medicine and Biology Society (EMBS), 2010 Annual International Conference of the IEEE . vol. 2010, IEEE Computer Society, pp. 6341-4. DOI: 10.1109/IEMBS.2010.5627637

Costa, RP, Watt, AJ & Sjöström, PJ 2013, 'How to train a neuron' eLIFE, vol. 2. DOI: 10.7554/eLife.00491

Costa, RP, Sjöström, PJ & van Rossum, MCW 2013, 'Probabilistic Inference of Short-Term Synaptic Plasticity in Neocortical Microcircuits' Frontiers in Computational Neuroscience, vol. 7, no. 75. DOI: 10.3389/fncom.2013.00075

Blackman, AV, Abrahamsson, T, Costa, RP, Lalanne, T & Sjöström, PJ 2013, 'Target Cell-Specific Short-Term Plasticity in Local Circuits' Frontiers in synaptic neuroscience, vol. 5, no. 11. DOI: 10.3389/fnsyn.2013.00011

Buchanan, KA, Blackman, AV, Moreau, AW, Elgar, D, Costa, RP, Lalanne, T, Tudor Jones, AA, Oyrer, J & Sjostrom, PJ 2012, 'Target-Specific Expression of Presynaptic NMDA Receptors in Neocortical Microcircuits' Neuron, vol. 75, no. 3, pp. 451-466. DOI: 10.1016/j.neuron.2012.06.017

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Philippides, A, Dewar, A, Wystrach, A, Mangan, M & Graham, P 2013, How active vision facilitates familiarity-based homing. in Biomimetic and Biohybrid Systems: Second International Conference, Living Machines 2013, London, UK, July 29 – August 2, 2013. Proceedings. Lecture Notes in Computer Science, vol. 8064, Springer Berlin Heidelberg, pp. 427-430. DOI: 10.1007/978-3-642-39802-5_56

Philippides, A, Wystrach, A, Mangan, M, Baddeley, B & Graham, P 2013, 'Models of visual navigation in ants' Frontiers in Psychology. DOI: 10.3389/conf.fphys.2013.25.00060

Wystrach, A, Mangan, M & Webb, B 2015, 'Optimal cue integration in ants' Proceedings of the Royal Society B: Biological Sciences, vol. 282, no. 1816. DOI: 10.1098/rspb.2015.1484

Mangan, M & Khodshabashev, A 2015, Route Following Without Scanning. in Biomimetic and Biohybrid Systems. vol. 9222, pp. 199-210. DOI: 10.1007/978-3-319-22979-9_20

Cheung, A, Collett, M, Collett, TS, Dewar, A, Dyer, F, Graham, P, Mangan, M, Narendra, A, Philippides, A, Stürzl, W, Webb, B, Wystrach, A & Zeil, J 2014, 'Still no convincing evidence for cognitive map use by honeybees' Proceedings of the National Academy of Sciences, vol. 111, no. 42, pp. E4396-E4397. DOI: 10.1073/pnas.1413581111

Haferlach, T, Wessnitzer, J, Mangan, M & Webb, B 2007, 'Evolving a Neural Model of Insect Path Integration' Adaptive Behavior, vol. 15, no. 3, pp. 273-287. DOI: 10.1177/1059712307082080

Wystrach, A, Mangan, M, Philippides, A & Graham, P 2013, 'Snapshots in ants? New interpretations of paradigmatic experiments' Journal of Experimental Biology, vol. 216, no. 10, pp. 1766-1770. DOI: 10.1242/jeb.082941

Mangan, M & Webb, B 2012, 'Spontaneous formation of multiple routes in individual desert ants (Cataglyphis velox)' Behavioral Ecology, vol. 23, no. 5, pp. 944-954. DOI: 10.1093/beheco/ars051

Wessnitzer, J, Mangan, M & Webb, B 2008, 'Place memory in crickets' Proceedings of the Royal Society B-Biological Sciences, vol. 275, no. 1637, pp. 915-921. DOI: 10.1098/rspb.2007.1647

Wessnitzer, J, Haferlach, T, Mangan, M & Webb, B 2008, 'Path Integration Using a Model of e-Vector Orientation Coding in the Insect Brain: Reply to Vickerstaff and Di Paolo' Adaptive Behavior, vol. 16, no. 4, pp. 277-280. DOI: 10.1177/1059712308094947

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Keemink, S, Lowe, S, Pakan, J, Dylda, E, Van Rossum, M & Rochefort, N 2018, 'FISSA: A neuropil decontamination toolbox for calcium imaging signals' Nature Human Behaviour. DOI: 10.1038/s41598-018-21640-2

Puggioni , P, Jelitai, M, Duguid, I & Van Rossum, M 2017, 'Extraction of synaptic input properties in vivo' Neural Computation. DOI: 10.1162/NECO_a_00975

Chadwick, A, van Rossum, MC & Nolan, MF 2016, 'Flexible theta sequence compression mediated via phase precessing interneurons' eLIFE, vol. 5. DOI: 10.7554/eLife.20349

Keck, T, Toyoizumi, T, Chen, L, Doiron, B, Feldman, DE, Fox, K, Gerstner, WG, Haydon, PG, Hübener, M, Lee, H-K, Lisman, JE, Rose, T, Sengpiel, F, Stellwagen, D, Stryker, MP, Turrigiano, GG & Van Rossum, M 2017, 'Integrating Hebbian and homeostatic plasticity: the current state of the field and future research directions' Philosophical Transactions of the Royal Society B: Biological Sciences, vol. 372, no. 1715. DOI: 10.1098/rstb.2016.0158

Costa, RP, Mizusaki, BEP, Sjöström, PJ & Van Rossum, M 2017, 'Functional consequences of pre- and postsynaptic expression of 2 synaptic plasticity' Philosophical Transactions of the Royal Society B: Biological Sciences, vol. 372, no. 1715, pp. 1-10. DOI: 10.1098/rstb.2016.0153

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Boer, JFD, Van Rossum, MCW, Albada, MPV, Nieuwenhuizen, TM & Lagendijk, A 1994, Non-Gaussian probability distribution of the total transmission of multiply scattered light. in International Quantum Electronics Conference 1994., QThE5, Optical Society of America (OSA).

Van Rossum, MCW & Smith, RG 1998, Noise Removal by Nonlinear Synapses. in JM Bower (ed.), Computational Neuroscience: Trends in Research, 1998. Springer US, Boston, MA, pp. 297-302. DOI: 10.1007/978-1-4615-4831-7_50

Brunel, N & Van Rossum, MCW 2007, 'Quantitative investigations of electrical nerve excitation treated as polarization' Biological Cybernetics, vol. 97, no. 5, pp. 341-349. DOI: 10.1007/s00422-007-0189-6

Van Rossum, MCW 2011, 'Representational capacity of neural codes in the cortex' Frontiers in Computational Neuroscience, no. 7. DOI: 10.3389/conf.fncom.2011.53.00007

Keemink, S & van Rossum, MCW 2016, 'A unified account of tilt illusions, association fields, and contour detection based on elastica' Vision Research, vol. 126, pp. 164–173. DOI: 10.1016/j.visres.2015.05.021

Sacramento, J, Wichert, A & van Rossum, MCW 2015, 'Energy Efficient Sparse Connectivity from Imbalanced Synaptic Plasticity Rules' PLoS Computational Biology, vol. 11, no. 6, e1004265. DOI: 10.1371/journal.pcbi.1004265

Keemink, S & Van Rossum, M 2014, 'Saliency detection without biasing stimulus estimation' Visual Image Interpretation in Humans and Machines, Stratford-Upon-Avon, United Kingdom, 24/09/14 - 25/09/14, .

Keemink, S & Van Rossum, M 2014, 'Coding and decoding from neural populations representing multiple stimuli' AREADNE 2014 Research in Encoding And Decoding of Neural Ensembles, Santorini, Greece, 25/06/14 - 29/06/14, .

Keemink, S, Boucsein, C & van Rossum, MCW 2013, 'Contextual interactions and association fields in a V1 network encoding a Bayesian posterior' The Bernstein Conference on Computational Neuroscience 2013, Tübingen, Germany, 24/09/13 - 27/09/13, .

Keemink, S, Boucsein, C & van Rossum, MCW 2013, 'Stimulus dependency of surround modulation in V1 allows for unbiased orientation decoding' Society for Neuroscience Annual Meeting 2013, San Diego, United States, 9/11/13 - 13/11/13, .

Keemink, S, Boucsein, C & van Rossum, MCW 2013, 'Impact of orientation specific surround modulation and tuning curve shape on population coding and tilt illusion in V1' 22nd Annual Computational Neuroscience Meeting: CNS 2013, Paris, France, 13/07/13 - 18/07/13, .

Esposito, U, Giugliano, M, van Rossum, M & Vasilaki, E 2014, 'Measuring Symmetry, Asymmetry and Randomness in Neural Network Connectivity' PLoS One, vol. 9, no. 7, 100805. DOI: 10.1371/journal.pone.0100805

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Janowitz, MK & van Rossum, MCW 2006, 'Excitability changes that complement Hebbian learning.' Network: Computation in Neural Systems, vol. 17, no. 1, pp. 31 - 41. DOI: 10.1080/09548980500286797

Kepecs, A, van Rossum, MCW, Song, S & Tegner, J 2002, 'Spike-timing-dependent plasticity: common themes and divergent vistas' Biological Cybernetics, vol. 87, pp. 446-458. DOI: 10.1007/s00422-002-0358-6

van Rossum, MCW & Renart, A 2004, 'Computation with populations codes in layered networks of integrate-and-fire neurons' Neurocomputing, vol. 58-60, no. 0, pp. 265 - 270. DOI: 10.1016/j.neucom.2004.01.054

Van Rossum, M & Smith, RG 1998, 'Noise removal at the rod synapse of mammalian retina' Visual Neuroscience, vol. 15, pp. 809-821. DOI: 10.1017/S0952523898155037

van Rossum, MCW, O'Brien, BJ & Smith, RG 2003, 'Effects of Noise on the Spike Timing Precision of Retinal Ganglion Cells' Journal of Neurophysiology, vol. 89, no. 5, pp. 2406-2419. DOI: 10.1152/jn.01106.2002

van Rossum, MCW, Turrigiano, GG & Nelson, SB 2002, 'Fast Propagation of Firing Rates through Layered Networks of Noisy Neurons' The Journal of Neuroscience, vol. 22, no. 5, pp. 1956-1966.

Watt, AJ, van Rossum, MCW, MacLeod, KM, Nelson, SB & Turrigiano, GG 2000, 'Activity coregulates quantal AMPA and NMDA currents at neocortical synapses' Neuron, vol. 26, no. 3, pp. 659-670. DOI: 10.1016/S0896-6273(00)81202-7

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Kilman, VL, van Rossum, MCW & Turrigiano, GG 2002, 'Activity Deprivation Reduces Miniature IPSC Amplitude by Decreasing the Number of Postsynaptic GABAA Receptors Clustered at Neocortical Synapses' The Journal of Neuroscience, vol. 22, no. 4, pp. 1328-1337.

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Van Rossum, MCW 2001, 'The Transient Precision of Integrate and Fire Neurons: Effect of Background Activity and Noise' Journal of Computational Neuroscience, vol. 10, no. 3, pp. 303-311. DOI: 10.1023/A:1011268215708

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Nezis, P & van Rossum, MCW 2011, 'Accurate multiplication with noisy spiking neurons' Journal of Neural Engineering, vol. 8, no. 3, 034005. DOI: 10.1088/1741-2560/8/3/034005

Renart, A & van Rossum, MCW 2012, 'Transmission of population-coded information' Neural Computation, vol. 24, no. 2, pp. 391-407. DOI: 10.1162/NECO_a_00227

Barrett, AB & van Rossum, MCW 2008, 'Optimal Learning Rules for Discrete Synapses' PLoS Computational Biology, vol. 4, no. 11, e1000230, pp. 1-7. DOI: 10.1371/journal.pcbi.1000230

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Bednar, J & Williams, CKI 2016, Neural Maps: Their Function and Development. in M Arbib & J Bonaiuto (eds), From Neuron to Cognition via Computational > Neuroscience. MIT Press, pp. 409-432.

Bednar, JA & Miikkulainen, R 2003, 'Joint maps for orientation, ocular dominance, and direction preference in a self-organizing laterally connected model of primary visual cortex' Society for Neuroscience Annual Meeting, 2003, New Orleans, Louisiana, United States, 4/11/03 - 9/11/03, .

Miikkulainen, R, Bednar, JA & Choe, Y 2004, 'Sparse, redundancy-reduced visual coding through self-organized lateral connections' Society for Neuroscience 2004, San Diego, CA, United States, 23/10/04 - 27/10/04, .

Bednar, JA 2000, 'Internally-generated activity, non-episodic memory, and emotional salience in sleep' Behavioral and Brain Sciences, vol. 23, no. 6, pp. 908-909. DOI: 10.1017/S0140525X0023402X

De Paula, JB, Bednar, JA & Miikkulainen, R 2004, 'Modeling self-organization of color-opponent receptive fields and laterally connected orientation maps and color blobs in V1' Society for Neuroscience 2004, San Diego, CA, United States, 23/10/04 - 27/10/04, .

Bednar, JA, Choe, Y, De Paula, J, Miikkulainen, R & Provost, J 2005, 'The Topographica cortical map simulator' 28th European Conference on Visual Perception, A Coruna, Spain, 22/08/05 - 26/08/05, .

Bednar, J, Choe, Y, De Paula, J, Miikkulainen, R & Provost, J 2005, 'Modeling the visual cortex using the Topographica cortical map simulator' Society for Neuroscience Annual Meeting, 2005, Washington DC, United States, 12/11/05 - 16/11/05, .

De Paula, J, Bednar, J & Miikkulainen, R 2007, 'Modeling self-organizing tri-chromatic color selective regions in primary visual cortex' BMC Neuroscience, vol. 8, no. Suppl 2, pp. S24. DOI: 10.1186/1471-2202-8-S2-S24

Wilson, SP & Bednar, JA 2015, 'What, if anything, are topological maps for?' Developmental neurobiology. DOI: 10.1002/dneu.22281

Perrinet, LU & Bednar, JA 2014, 'Edge co-occurrences are sufficient to categorize natural versus animal images' Journal of Vision, vol. 14, no. 10, pp. 1310-1310. DOI: 10.1167/14.10.1310

Davison, AP, Diesmann, M, Gewaltig, M-O, Ghosh, SS, Perez, F, Muller, E, Bednar, JA, Thirion, B & Halchenko, Y (eds) 2015, Python in Neuroscience II. Frontiers Media SA.

Bednar, JA, Kelkar, A & Miikkulainen, R 2002, 'Modeling large cortical networks with growing self-organizing maps' Neurocomputing, pp. 315-321. DOI: 10.1016/S0925-2312(02)00358-2

Bednar, J, Wilson, SP, Mitchinson, B, Pearson, M & Prescott, TJ 2009, 'Learning multi-whisker spatial-temporal cortical receptive fields from robotic whisker input' Society for Neuroscience Annual Meeting 2009, Chicago, United States, 17/10/09 - 21/10/09, .

Wilson, SP, Mitchinson, B, Pearson, M, Bednar, JA & Prescott, TJ 2009, 'Learning cortical representations from multiple whisker inputs' BMC Neuroscience, vol. 10, no. Suppl 1, pp. P334. DOI: 10.1186/1471-2202-10-S1-P334

Bednar, J, Wilson, SP, Mitchinson, B & Prescott, TJ 2012, 'Orthogonal coding of tactile stimulus features in a self-organising model of barrel cortex development' 8th Fens Forum of Neuroscience, Barcelona, Spain, 14/07/12 - 18/07/12, .

Bednar, J, Perrinet, L & David, F 2011, 'Edge statistics in natural images versus laboratory animal environments: Implications for understanding lateral connectivity in V1' Neuroscience 2011, Washington, DC, United States, 12/11/11 - 16/11/11, .

Bednar, JA & Miikkulainen, R 1997, A Neural Network Model of Visual Tilt Aftereffects. in MG Shafto & P Langley (eds), In Proceedings of the 19th Annual Conference of the Cognitive Science Society. Erlbaum, pp. 37-42.

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Bednar, JA & Miikkulainen, R 1998, Pattern-Generator-Driven Development In Self-Organizing Models. in JM Bower (ed.), Computational Neuroscience: Trends in Research, 1998. Plenum Press, pp. 317-323.

Bednar, JA & Miikkulainen, R 2000, Self-Organization of Innate Face Preferences: Could Genetics Be Expressed Through Learning? in Proceedings of the Seventeenth National Conference on Artificial Intelligence. AAAI Press, pp. 117-122.

Bednar, JA 2012, Visual Cortex as a General-Purpose Information-Processing Device. in A Fusiello, V Murino & R Cucchiara (eds), Computer Vision – ECCV 2012. Workshops and Demonstrations: Florence, Italy, October 7-13, 2012, Proceedings, Part I. Springer Berlin Heidelberg, pp. 480-485. DOI: 10.1007/978-3-642-33863-2_49

Sirosh, J, Miikkulainen, R & Bednar, JA 1996, Self-Organization of Orientation Maps, Lateral Connections, and Dynamic Receptive Fields in the Primary Visual Cortex. in J Sirosh, R Miikkulainen & Y Choe (eds), Proceedings of the International Conference on Artificial Neural Networks. Springer Japan, Berlin, pp. 1147-1152.

Miikkulainen, R, Bednar, JA, Choe, Y & Sirosh, J 1997, Self-Organization, Plasticity, and Low-Level Visual Phenomena in a Laterally Connected Map Model of the Primary Visual Cortex. in RL Goldstone, PG Schyns & DL Medin (eds), Perceptual Learning. Psychology of Learning and Motivation, Academic Press, pp. 257-308.

Miikkulainen, R, Bednar, J, Choe, Y & Sirosh, J 1999, Modeling Self-Organization in the Visual Cortex. in E Oja & S Kaski (eds), Kohonen Maps. ELSEVIER SCIENCE PUBL B V, pp. 243-252. DOI: 10.1016/B978-044450270-4/50019-X

Bednar, J 2003, The Role of Internally Generated Neural Activity in Newborn and Infant Face Preferences. in O Pascalis & A Slater (eds), The Development of Face Processing in Infancy and Early Childhood: Current Perspectives. Nova Science Publishers, pp. 133-142.

Bednar, JA & Miikkulainen, R 2005, Constructing visual function through prenatal and postnatal learning. in D Mareschal, MH Johnson, S Sirois, M Spratling, MSC Thomas & G Westermann (eds), Neuroconstructivism, Vol. 2: Perspectives and Prospects. Oxford University Press, pp. 13-37.

Bednar, JA 2014, Constructing Complex Systems Via Activity-Driven Unsupervised Hebbian Self-Organization. in T Kowaliw, N Bredeche & R Doursat (eds), Growing Adaptive Machines: Combining Development and Learning in Artificial Neural Networks. vol. 557, Growing Adaptive Machines, vol. 557, Springer Berlin Heidelberg, pp. 201-225. DOI: 10.1007/978-3-642-55337-0_7

Bednar, J 2014, Visual Aftereffects, Models of. in D Jaeger & R Jung (eds), Encyclopedia of Computational Neuroscience. Springer New York, pp. 1-8. DOI: 10.1007/978-1-4614-7320-6_730-1

Bednar, JA 2014, Topographica. in D Jaeger & R Jung (eds), Encyclopedia of Computational Neuroscience. Springer New York, New York, NY, pp. 1-5. DOI: 10.1007/978-1-4614-7320-6_263-5

Bednar, JA 2014, Hebbian Learning of the Statistical and Geometrical Structure of Visual Input. in Neuromathematics of Vision: Lecture Notes in Morphogenesis., Chapter 8, Neuromathematics of Vision, Springer Berlin Heidelberg, pp. 335-366. DOI: 10.1007/978-3-642-34444-2_8

Miikkulainen, R, Bednar, J, Choe, Y & Sirosh, J 2005, Computational Maps in the Visual Cortex. Springer New York, New York. DOI: 10.1007/0-387-28806-6

Gewaltig, M-O, Hines, M, Koetter, R, Diesmann, M, Davison, AP, Muller, E & Bednar, J (eds) 2009, Python in Neuroscience. Frontiers Media SA.

Bednar, JA & Miikkulainen, R 2004, 'Prenatal and postnatal development of laterally connected orientation maps' Neurocomputing, vol. 58-60, pp. 985-992. DOI: 10.1016/j.neucom.2004.01.156

Bednar, JA, Choe, Y, Paula, JD, Miikkulainen, R, Provost, J & Tversky, T 2004, 'Modeling Cortical Maps with Topographica' Neurocomputing, vol. 58-60, pp. 1129-1135. DOI: 10.1016/j.neucom.2004.01.177

Bednar, JA & Miikkulainen, R 2002, Neonatal Learning of Faces: Environmental and Genetic Influences. in Proceedings of the 24th Annual Conference of the Cognitive Science Society. pp. 107-112.

Bednar, JA & Miikkulainen, R 2003, Self-Organization of Spatiotemporal Receptive Fields and laterally connected direction and orientation maps. in Neurocomputing. Thoemmes Press, pp. 52-54.

Valsalam, V, Bednar, J & Miikkulainen, R 2005, Constructing Good Learners Using Evolved Pattern Generators. in Proceedings of the 7th Annual Conference on Genetic and Evolutionary Computation. GECCO '05, ACM, New York, NY, USA, pp. 11-18. DOI: 10.1145/1068009.1068012

Bednar, JA, De Paula, JB & Miikkulainen, R 2005, 'Self-organization of Color Opponent Receptive Fields and Laterally Connected Orientation Maps' Neurocomputing, pp. 69-76. DOI: 10.1016/j.neucom.2004.10.055

Valsalam, VK, Bednar, JA & Miikkulainen, R 2006, Establishing an Appropriate Learning Bias Through Development. in Proceedings of the Fifth International Conference on Development and Learning (ICDL-2006).

Jegelka, S, Bednar, JA & Miikkulainen, R 2006, 'Prenatal Development of Ocular Dominance and Orientation Maps in a Self-Organizing Model of V1' Neurocomputing, vol. 69, pp. 1291-1296.

Bednar, JA & Miikkulainen, R 2006, 'Joint Maps for Orientation, Eye, and Direction Preference in a Self-Organizing Model of V1' Neurocomputing, vol. 69, pp. 1272-1276.

Bednar, JA & Miikkulainen, R 2000, 'Tilt Aftereffects In A Self-Organizing Model Of The Primary Visual Cortex' Neural Computation, vol. 12, pp. 1721-1740.

Bednar, JA & Miikkulainen, R 2003, 'Learning Innate Face Preferences' Neural Computation, vol. 15, no. 7, pp. 1525-1557.

Bednar, JA, Kelkar, A & Miikkulainen, R 2001, 'Scaling Self-Organizing Maps To Model Large Cortical Networks' Neuroinformatics, pp. 275-302.

Valsalam, VK, Bednar, JA & Miikkulainen, R 2007, 'Developing Complex Systems Using Evolved Pattern Generators' IEEE Transactions on Evolutionary Computation, pp. 181-198.

Bednar, JA 2008, 'Understanding Neural Maps with Topographica' Brains, Minds & Media, no. 1.

Crook, SM, Bednar, JA, Berger, S, Cannon, R, Davison, AP, Djurfeldt, M, Eppler, J, Kriener, B, Furber, S, Graham, B, Plesser, HE, Schwabe, L, Smith, L, Steuber, V & van Albada, S 2012, 'Creating, documenting and sharing network models' Network: Computation in Neural Systems, vol. 23, no. 4, pp. 131-149. DOI: 10.3109/0954898X.2012.722743

Bednar, JA 2012, 'Building a mechanistic model of the development and function of the primary visual cortex' Journal of Physiology-Paris, vol. 106, no. 5-6, pp. 194-211. DOI: 10.1016/j.jphysparis.2011.12.001

Wilson, SP, Bednar, JA, Prescott, TJ & Mitchinson, B 2011, 'Neural Computation via Neural Geometry: A Place Code for Inter-Whisker Timing in the Barrel Cortex?' PLoS Computational Biology, vol. 7, no. 10, e1002188. DOI: 10.1371/journal.pcbi.1002188

Bednar, JA 2009, 'Topographica: building and analyzing map-level simulations from Python, C/C++, MATLAB, NEST, or NEURON components' Frontiers in Neuroinformatics, vol. 3, no. 8, 8, pp. 1-9. DOI: 10.3389/neuro.11.008.2009

Malhotra, G, Pickering, MJ, Branigan, HP & Bednar, JA 2008, On the persistence of Structural priming: mechanisms of decay and Influence of word-Forms. in Proceedings of the 30th Annual Conference of the Cognitive Science Society. Cognitive Science Society, pp. 657-662.

Mourao, K 2014, Learning probabilistic planning operators from noisy observations. in 31st Workshop of the UK Planning & Scheduling Special Interest Group (PlanSIG 2013).

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Mourao, K, Steedman, M & Donaldson, DI 2007, 'Effects of sentence structure on sentence processing - an ERP study'.

Mourao, K, Steedman, M & Donaldson, DI 2006, 'From Intonation to Information - an ERP study'.

Mourao, K & Petrick, R 2013, Learning Knowledge-Level Domain Dynamics. in Proceedings of the ICAPS 2013 Workshop on Planning and Learning. pp. 23-31.

Mourao, K, Petrick, R & Steedman, M 2010, Learning action effects in partially observable domains. in H Coelho, R Studer & M Wooldridge (eds), ECAI 2010 - 19th European Conference on Artificial Intelligence, Lisbon, Portugal, August 16-20, 2010, Proceedings.. IOS Press, pp. 973-974. DOI: 10.3233/978-1-60750-606-5-973

Mourao, K, Petrick, R & Steedman, M 2009, Learning action effects in partially observable domains. in Proceedings of the ICAPS 2009 Workshop on Planning and Learning. pp. 15-22.

Mourao, K, Petrick, R & Steedman, M 2008, Using Kernel Perceptrons to Learn Action Effects for Planning. in Proceedings of the International Conference on Cognitive Systems (CogSys 2008). pp. 45-50.

Petrick, R, Kraft, D, Mourao, K, Geib, C, Pugeault, N, Krüger, N & Steedman, M 2008, Representation and Integration: Combining Robot Control, High-Level Planning, and Action Learning. in Proceedings of the International Cognitive Robotics Workshop (CogRob 2008) at ECAI 2008. pp. 32-41.

Geib, C, Mourao, K, Petrick, R, Pugeault, N, Steedman, M, Krüger, N & Wörgötter, F 2006, Object Action Complexes as an Interface for Planning and Robot Control. in IEEE-RAS Humanoids-06 Workshop: Towards Cognitive Humanoid Robots.

Mourao, K, Zettlemoyer, L, Petrick, R & Steedman, M 2012, Learning STRIPS Operators from Noisy and Incomplete Observations. in Proceedings of the Twenty Eighth Conference on Uncertainty in Artificial Intelligence (UAI 2012). pp. 614-623.

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Karvelis, P, Seitz, AR, Lawrie, S & Series, P 2018, 'Autistic traits, but not schizotypy, predict increased weighting of sensory information in Bayesian visual integration' eLIFE. DOI: 10.7554/eLife.34115

Cohen Hoffing, R, Karvelis, P, Rupprechter, S, Seriès, P & Seitz, AR 2018, 'The Influence of Feedback on Task-Switching Performance: A Drift Diffusion Modeling Account' Frontiers in integrative neuroscience, vol. 12, no. 1. DOI: 10.3389/fnint.2018.00001

Raymond, JG, Steele, JD & Seriès, P 2017, 'Modeling Trait Anxiety: From Computational Processes to Personality' Frontiers in psychiatry, vol. 8, 1, pp. 1-19. DOI: 10.3389/fpsyt.2017.00001

Series, P 2017, 'Conditioned Task-set Competition: Neural Mechanisms of Emotional Interference in Depression' Cognitive, affective & behavioral neuroscience, pp. 1-21. DOI: 10.3758/s13415-016-0478-4

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