Edinburgh Research Explorer

Institute for Adaptive and Neural Computation

Organisational unit: Research Institute

  1. Human Nonverbal Behaviour Understanding in the Wild for New Media Art

    Morgan, E. & Gunes, H., 2013, Human Behavior Understanding: 4th International Workshop, HBU 2013, Barcelona, Spain, October 22, 2013. Proceedings. Salah, A. A., Hung, H., Aran, O. & Gunes, H. (eds.). Cham: Springer International Publishing, p. 27-39 13 p. (Lecture Notes in Computer Science; vol. 8212).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  2. Hybrid regulatory models: a statistically tractable approach to model regulatory network dynamics

    Ocone, A., Millar, A. J. & Sanguinetti, G., 2013, In : Bioinformatics. 29, 7, p. 910-916 7 p.

    Research output: Contribution to journalArticle

  3. IMAGE ANALYSIS FOR COSMOLOGY: RESULTS FROM THE GREAT10 STAR CHALLENGE

    Kitching, T. D., Rowe, B., Gill, M., Heymans, C., Massey, R., Witherick, D., Courbin, F., Georgatzis, K., Gentile, M., Gruen, D., Kilbinger, M., Li, G. L., Mariglis, A. P., Meylan, G., Storkey, A. & Xin, B., Apr 2013, In : The Astrophysical Journal Supplement Series. 205, 2, 11 p., 12.

    Research output: Contribution to journalArticle

  4. Identifying GFP-transgenic animals by flashlight

    Tyas, D. A., Pratt, T., Simpson, T. I., Mason, J. O. & Price, D. J., 2003, In : Biotechniques. 34, 3, p. 474-6 3 p.

    Research output: Contribution to journalArticle

  5. Identifying Submodules of Cellular Regulatory Networks

    Sanguinetti, G., Rattray, M. & Lawrence, N. D., 2006, Computational Methods in Systems Biology. Priami, C. (ed.). Springer Berlin Heidelberg, p. 155-168 14 p. (Lecture Notes in Computer Science; vol. 4210).

    Research output: Chapter in Book/Report/Conference proceedingChapter

  6. Identifying differentially expressed subnetworks with MMG

    Noirel, J., Sanguinetti, G. & Wright, P. C., Dec 2008, In : Bioinformatics. 24, 23, p. 2792-2793 2 p.

    Research output: Contribution to journalArticle

  7. Identifying semi-Invariant Features on Mouse Contours

    Crook, P. A., Lukins, T. C., Heward, J. & Armstrong, J. D., 2008, Proceedings of the British Machine Vision Conference. BMVA Press, p. 84.1-84.10 10 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  8. ImaGen: Generic library for 0D, 1D and 2D pattern distributions

    Bednar, J. A. & Ball, C. E., 2012.

    Research output: Contribution to conferencePoster

  9. Image modeling with position-encoding dynamic trees

    Storkey, AJ. & Williams, CKI., Jul 2003, In : IEEE Transactions on Pattern Analysis and Machine Intelligence. 25, 7, p. 859-871 13 p.

    Research output: Contribution to journalArticle

  10. Impaired artificial grammar learning in agrammatism

    Christiansen, M. H., Louise Kelly, M., Shillcock, R. C. & Greenfield, K., 1 Sep 2010, In : Cognition. 116, 3, p. 382-393 12 p.

    Research output: Contribution to journalArticle

  11. Implications of noise and neural heterogeneity for vestibulo-ocular reflex fidelity

    Hospedales, T., van Rossum, M. C. W., Graham, B. P. & Dutia, M. B., Mar 2008, In : Neural Computation. 20, 3, p. 756-778 23 p.

    Research output: Contribution to journalArticle

  12. Improved Dynamic Schedules for Belief Propagation

    Sutton, C. & McCallum, A., 2007, Proceedings of the Twenty-Third Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-07). Corvallis, Oregon: AUAI Press, p. 376-383 8 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  13. Improved Functional Enrichment Analysis of Biological Networks using Scalable Modularity Based Clustering

    Mclean, C., He, X., Simpson, I. T. & Armstrong, D. J., 31 Jan 2016, In : Journal of Proteomics & Bioinformatics. 9, 1, p. 9-18 10 p.

    Research output: Contribution to journalArticle

  14. Improved Rodent Contour Extraction Using A Priori Shape Information

    Sillito, R. R., Lukins, T. C. & Armstrong, J. D., 2010, Workshop on the Visual Observation and Analysis of Animal and Insect Behavior (held at ICPR2010). 4 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  15. Improved numberical methods for computing likelihoods in the stochastic integrate-and-fire model

    Paninski, L., Haith, A. M., Pillow, J. W. & Williams, C. K. I., 2005.

    Research output: Contribution to conferencePoster

  16. Improved segmentation reproducibility in group tractography using a quantitative tract similarity measure

    Clayden, J. D., Bastin, M. E. & Storkey, A. J., 2006, In : NeuroImage. 33, 2, p. 482-92 11 p.

    Research output: Contribution to journalArticle

  17. In Search of Art

    Crowley, E. J. & Zisserman, A., 2015, Computer Vision - ECCV 2014 Workshops: Zurich, Switzerland, September 6-7 and 12, 2014, Proceedings, Part I. Agapito, L., Bronstein, M. M. & Rother, C. (eds.). Cham: Springer International Publishing, p. 54-70 17 p. (Lecture Notes in Computer Science; vol. 8925).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  18. In vitro light distributions from intracranial PDT balloons

    Moseley, H., McLean, C., Hockaday, S. & Eljamel, S., Sep 2007, In : Photodiagnosis and Photodynamic Therapy. p. 213-220 8 p.

    Research output: Contribution to journalArticle

  19. Incorporating side information into probabilistic matrix factorization using Gaussian Processes

    Adams, R. P., Dahl, G. E. & Murray, I., 2010, Proceedings of the 26th Conference on Uncertainty in Artificial Intelligence (UAI 2010). 9 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  20. Individualized prediction of psychosis in subjects with an at-risk mental state

    Zarogianni, E., Storkey, A. J., Borgwardt, S., Smieskova, R., Studerus, E., Riecher-Rössler, A. & Lawrie, S. M., 19 Sep 2017, In : Schizophrenia Research.

    Research output: Contribution to journalArticle

  21. Inference and Learning in Networks of Queues

    Sutton, C. & Jordan, M. I., 2010, Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS) 2010. Journal of Machine Learning Research: Workshop and Conference Proceedings, p. 796-813 8 p. (JMLR Workshop and Conference Proceedings; vol. 9).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  22. Inference in continuous-time change-point models

    Stimberg, F., Opper, M., Sanguinetti, G. & Ruttor, A., 2011, Advances in Neural Information Processing Systems 24. Shawe-Taylor, J., Zemel, R. S., Bartlett, P. L., Pereira, F. & Weinberger, K. Q. (eds.). Curran Associates Inc, p. 2717-2725 9 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  23. Inference in hierarchical transcriptional network motifs

    Ocone, A. & Sanguinetti, G., 2010, Machine Learning in Systems Biology, Proceedings of the Fourth International Workshop of . p. 47-50 4 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  24. Inference of neuronal functional circuitry with spike-triggered non-negative matrix factorization

    Liu, J. K., Schreyer, H. M., Onken, A., Rozenblit, F., Khani, M. H., Krishnamoorthy, V., Panzeri, S. & Gollisch, T., 2017, In : Nature Communications. 8, 1, p. 1-14 14 p., 149.

    Research output: Contribution to journalArticle

  25. Influence of skin layers on speckle correlations of light transmitted through disordered media

    van Rossum, M. & Nieuwenhuizen, T. M., 1993, In : Physics letters a. 177, 6, p. 452 - 458 7 p.

    Research output: Contribution to journalArticle

  26. Information Estimation Using Non-Parametric Copulas

    Safaai, H., Onken, A., Harvey, C. & Panzeri, S., 10 Oct 2018, (Accepted/In press) In : Physical Review E. 17 p.

    Research output: Contribution to journalArticle

  27. Information theoretic novelty detection

    Filippone, M. & Sanguinetti, G., 2010, In : Pattern Recognition. 43, 3, p. 805 - 814 10 p.

    Research output: Contribution to journalArticle

  28. Information theory and representation in associative word learning

    Burns, B., Sutton, C., Morrison, C. & Cohen, P., 2003, Proceedings of the Third International Workshop on Epigenetic Robotics. 7 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  29. Inhomogeneities in Heteroassociative Memories with Linear Learning Rules

    Willshaw, D. & Sterratt, D., Feb 2008, In : Neural Computation. 20, 2, p. 311-344 34 p.

    Research output: Contribution to journalArticle

  30. Inner hemifoveas preferred for words briefly presented stereoscopically

    Obregón, M., Dare, N. & Shillcock, R. C., 1 Jul 2008. 1 p.

    Research output: Contribution to conferenceAbstract

  31. Input-Output Non-Linear Dynamical Systems applied to Physiological Condition Monitoring

    Georgatzis, K., Williams, C. K. I. & Hawthorne, C., 20 Aug 2016, Proceedings of Machine Learning for Healthcare 2016: JMLR W&C Track Volume 56. Journal of Machine Learning Research: Workshop and Conference Proceedings, Vol. 56. 16 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  32. Instantiating Deformable Models with a Neural Net

    Williams, C. K. I., Revow, M. & Hinton, G. E., Oct 1997, In : Computer Vision and Image Understanding. 68, 1, p. 120-126 7 p.

    Research output: Contribution to journalArticle

  33. Instrumenting the Interaction: Affective and Psychophysiological Features of Live Collaborative Musical Improvisation

    Morgan, E., Gunes, H. & Bryan-Kinns, N., 2014, Proceedings of the International Conference on New Interfaces for Musical Expression NIME 14. p. 23-28 6 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  34. Integrating Hebbian and homeostatic plasticity: the current state of the field and future research directions

    Keck, T., Toyoizumi, T., Chen, L., Doiron, B., Feldman, D. E., Fox, K., Gerstner, W. G., Haydon, P. G., Hübener, M., Lee, H-K., Lisman, J. E., Rose, T., Sengpiel, F., Stellwagen, D., Stryker, M. P., Turrigiano, G. G. & Van Rossum, M., 16 Jan 2017, In : Philosophical Transactions of the Royal Society B: Biological Sciences. 372, 1715, 23 p.

    Research output: Contribution to journalArticle

  35. Integration of rule-based models and compartmental models of neurons

    Sterratt, D. C., Sorokina, O. & Armstrong, J. D., 2014, Hybrid Systems and Biology: Second International Workshop, HSB 2013, Taormina, Italy, September 2, 2013 and Third International Workshop, HSB 2014, Vienna, Austria, July 23-24, 2014, Revised Selected Papers. Springer International Publishing, p. 143-158 16 p. (Lecture Notes in Computer Science; vol. 7699).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  36. Intensity Distributions of Waves Transmitted through a Multiple Scattering Medium

    Nieuwenhuizen, T. M. & van Rossum, M. C. W., 1 Apr 1995, In : Physical Review Letters. 74, p. 2674-2677 4 p.

    Research output: Contribution to journalArticle

  37. Inter-Individual behavioural traits shape performances in decision making

    Valton, V., Marchand, A., Dellu-Hagedom, F. & Series, P., 2010.

    Research output: Contribution to conferencePoster

  38. Interactions between multiple sources of short term plasticity during evoked and spontaneous activity at the rat calyx of Held

    Hennig, M., Graham, B. P., Postlethwaite, M. & Forsythe, I. D., Jul 2008, In : Journal of Physiology. 586, 13, p. 3129-3146 18 p.

    Research output: Contribution to journalArticle

  39. Internally-generated activity, non-episodic memory, and emotional salience in sleep

    Bednar, J. A., 1 Dec 2000, In : Behavioral and Brain Sciences. 23, 6, p. 908-909

    Research output: Contribution to journalArticle

  40. Interpretable Machine Teaching via Feature Feedback

    Su, S., Chen, Y., Mac Aodha, O., Perona, P. & Yue, Y., 9 Dec 2017. 9 p.

    Research output: Contribution to conferencePaper

  41. Introduction: Trends and convergences in language acquisition research (vol 106, pg 1, 1998)

    Sorace, A., Heycock, C., Shillcock, R. & Jusczyk, P., Feb 1999, In : Lingua. 107, 1-2, p. 161-161 1 p.

    Research output: Contribution to journalArticle

  42. Invent-abling: Enabling Inventiveness Through Craft

    Guler, S. D. & Rule, M. E., 2013, IDC '13 Proceedings of the 12th International Conference on Interaction Design and Children. New York, NY, USA: ACM, p. 368-371 4 p. (IDC '13).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  43. Inverting Supervised Representations with Autoregressive Neural Density Models

    Nash, C., Kushman, N. & Williams, C. K. I., 18 Apr 2019, Proceedings of the Twenty-Second International Conference on Artificial Intelligence and Statistics. Lawrence, N. & Reid, M. (eds.). PMLR, Vol. 89. 10 p. (Proceedings of Machine Learning Research).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  44. Investigating the specificity of experimentally induced expectations in motion perception

    Seitz, A., Seriès, P. & Gekas, N., 2012, In : Journal of Vision. 12, 9, p. 1137 1 p.

    Research output: Contribution to journalMeeting abstract

  45. Ionotropic Receptors Dynamics, Conductance Models

    Hennig, M., 2014, Encyclopedia of Computational Neuroscience. Jaeger, D. & Jung, R. (eds.). Springer New York, p. 1-5 5 p.

    Research output: Chapter in Book/Report/Conference proceedingEntry for encyclopedia/dictionary

  46. Is the Homunculus "Aware" of Sensory Adaptation?

    Seriés, P., Stocker, A. A. & Simoncelli, E. P., Dec 2009, In : Neural Computation. 21, 12, p. 3271-3304 34 p.

    Research output: Contribution to journalArticle

  47. Is there a burden attached to synaesthesia? Health screening of synaesthetes in the general population

    Carmichael, D., Smees, R., Shillcock, R. C. & Simner, J., 3 Oct 2018, In : British Journal of Psychology. p. 1-19 19 p.

    Research output: Contribution to journalArticle

  48. Isoelastic Agents and Wealth Updates in Machine Learning Markets

    Storkey, A., Millin, J. & Geras, K., 27 Jun 2012, Proceedings of the 29th International Conference on Machine Learning (ICML 2012). 8 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  49. It's all Relative: Monocular 3D Human Pose Estimation from Weakly Supervised Data

    Ruggero Ronchi, M., Mac Aodha, O., Eng, R. & Perona, P., 2 Sep 2018, p. 1-13. 13 p.

    Research output: Contribution to conferencePaper

  50. Joint Maps for Orientation, Eye, and Direction Preference in a Self-Organizing Model of V1

    Bednar, J. A. & Miikkulainen, R., 2006, In : Neurocomputing. 69, p. 1272-1276 5 p.

    Research output: Contribution to journalArticle

  51. Joint Parsing and Semantic Role Labeling

    Sutton, C. & McCallum, A., 1 Jun 2005, Proceedings of the Ninth Conference on Computational Natural Language Learning (CoNLL-2005). Ann Arbor, Michigan: Association for Computational Linguistics, p. 225-228 4 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  52. Kick-starting GPLVM Optimization via a Connection to Metric MDS

    Bitzer, S. & Williams, C. K. I., 2010, Proceedings of the NIPS 2010 workshop on Challenges of Data Visualization. 6 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  53. Kinetic CRAC uncovers a role for Nab3 in determining gene expression profiles during stress

    Van Nues, R., Schweikert, G., De Leau, E., Selega, A., Langford, A., Franklin, R., Iosub, I., Wadsworth, P., Sanguinetti, G. & Granneman, S., 11 Apr 2017, In : Nature Communications. 8, 12.

    Research output: Contribution to journalArticle

  54. Known Unknowns: Novelty Detection in Condition Monitoring

    Quinn, J. A. & Williams, C. K. I., 2007, Pattern Recognition and Image Analysis: Third Iberian Conference, IbPRIA 2007, Girona, Spain, June 6-8, 2007, Proceedings, Part I. Martí, J., Benedí, J. M., Mendonça, A. M. & Serrat, J. (eds.). Springer Berlin Heidelberg, p. 1-6 6 p. (Lecture Notes in Computer Science; vol. 4477).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  55. Language acquisition: knowledge representation and processing

    Heycock, C. B. (ed.), Shillcock, R. (ed.) & Sorace, A. (ed.), 1999, 1st ed. ed. Amsterdam: North-Holland Publishing Company. 263 p.

    Research output: Book/ReportBook

  56. Lapicque's 1907 paper: from frogs to integrate-and-fire

    Brunel, N. & van Rossum, M., 2007, In : Biological Cybernetics. 97, 5-6, p. 337-339 3 p.

    Research output: Contribution to journalArticle

  57. Large Developing Axonal Arbors Using a Distributed and Locally-Reprogrammable Address-Event Receiver

    Bamford, S., Murray, A. & Willshaw, D. J., 1 Jun 2008, IEEE International Joint Conference on Neural Networks (IJCNN). p. 1464-1471 8 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  58. Large Developing Receptive Fields Using a Distributed and Locally Reprogrammable Address-Event Receiver

    Bamford, S., Murray, A. & Willshaw, D. J., Feb 2010, In : IEEE Transactions on Neural Networks. 21, 2, p. 286-304 19 p.

    Research output: Contribution to journalArticle

  59. Large-Scale Study of Curiosity-Driven Learning

    Burda, Y., Edwards, H., Pathak, D., Storkey, A., Darrell, T. & Efros, A. A., 2019. 15 p.

    Research output: Contribution to conferencePaper

  60. Large-scale learning of combinatorial transcriptional dynamics from gene expression

    Asif, H. M. S. & Sanguinetti, G., 1 May 2011, In : Bioinformatics. 27, 9, p. 1277-1283 7 p.

    Research output: Contribution to journalArticle

  61. Latent Bayesian melding for integrating individual and population models

    Zhong, M., Goddard, N. & Sutton, C., 2015, Advances in Neural Information Processing Systems 28 (NIPS 2015). p. 3617-3625 9 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  62. Latent Variable Models

    Bishop, C. M., 1 Jan 1999, Learning in Graphical Models. Jordan, M. I. (ed.). MIT Press, p. 371–403 33 p. (Adaptive Computation and Machine Learning).

    Research output: Chapter in Book/Report/Conference proceedingChapter

  63. Latent Variables, Topographic Mappings and Data Visualization

    Bishop, C., 1998, Neural Nets WIRN VIETRI-97: Proceedings of the 9th Italian Workshop on Neural Nets, Vietri sul Mare, Salerno, Italy, 22–24 May 1997. Marinaro, M. & Tagliaferri, R. (eds.). Springer London, p. 3-32 30 p. (Perspectives in Neural Computing).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  64. Le cerveau est-il une machine Bayésienne

    Series, P., 2015, (Accepted/In press) Les méthodes bayésiennes, sciences et épistémologie. Drouet, I. (ed.). 16 p.

    Research output: Chapter in Book/Report/Conference proceedingChapter

  65. Learning Continuous Semantic Representations of Symbolic Expressions

    Allamanis, M., Chanthirasegaran, P., Kohli, P. & Sutton, C., 11 Aug 2017, The 34th International Conference on Machine Learning (ICML 2017). Sydney, Australia: PMLR, Vol. 70. p. 80-88 9 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  66. Learning Innate Face Preferences

    Bednar, J. A. & Miikkulainen, R., 2003, In : Neural Computation. 15, 7, p. 1525-1557 33 p.

    Research output: Contribution to journalArticle

  67. Learning Natural Coding Conventions

    Allamanis, M., Barr, E. T., Bird, C. & Sutton, C., 2014, Proceedings of the 22Nd ACM SIGSOFT International Symposium on Foundations of Software Engineering. New York, NY, USA: ACM, p. 281-293 13 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  68. Learning Natural Image Structure with a Horizontal Product Model

    Köster, U., Lindgren, J. T., Gutmann, M. & Hyvärinen, A., 2009, Independent Component Analysis and Signal Separation: 8th International Conference, ICA 2009, Paraty, Brazil, March 15-18, 2009. Proceedings. Adali, T., Jutten, C., Romano, J. M. T. & Barros, A. K. (eds.). Berlin, Heidelberg: Springer Berlin Heidelberg, p. 507-514 8 p. (Lecture Notes in Computer Science; vol. 5441).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  69. Learning Topographic Representations for Linearly Correlated Components

    Sasaki, H., Gutmann, M. U., Shouno, H. & Hyvärinen, A., 2011, Workshop on Deep Learning and Unsupervised Feature Learning, NIPS. 9 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  70. Learning a Confidence Measure for Optical Flow

    Mac Aodha, O., Humayun, A., Pollefeys, M. & Brostow, G. J., 31 May 2013, In : IEEE Transactions on Pattern Analysis and Machine Intelligence. 35, 5, p. 1107-1120 14 p.

    Research output: Contribution to journalArticle

  71. Learning a selectivity--invariance--selectivity feature extraction architecture for images

    Gutmann, M. U. & Hyvärinen, A., 2012, Pattern Recognition (ICPR), 2012 21st International Conference on. Institute of Electrical and Electronics Engineers (IEEE), p. 918-921 4 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  72. Learning analytics adoption – approaches and maturity

    Tsai, Y-S., Kovanović, V. & Gasevic, D., 3 Jan 2019, (Accepted/In press). 2 p.

    Research output: Contribution to conferencePoster

  73. Learning and Designing Stochastic Processes from Logical Constraints

    Bortolussi, L. & Sanguinetti, G., 2013, Quantitative Evaluation of Systems: 10th International Conference, QEST 2013, Buenos Aires, Argentina, August 27-30, 2013. Proceedings. Joshi, K., Siegle, M., Stoelinga, M. & D'Argenio, P. R. (eds.). Springer-Verlag GmbH, p. 89-105 17 p. (Lecture Notes in Computer Science; vol. 8054).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  74. Learning and Verifying Unwanted Behaviours

    Chen, W., Aspinall, D., Gordon, A., Sutton, C. & Muttik, I., 2016, 4th Workshop on Hot Issues in Security Principles and Trust (HotSpot 2016). p. 17-32 15 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  75. Learning combinatorial transcriptional dynamics from gene expression data

    Opper, M. & Sanguinetti, G., 1 Jul 2010, In : Bioinformatics. 26, 13, p. 1623-1629 7 p.

    Research output: Contribution to journalArticle

  76. Learning cortical representations from multiple whisker inputs

    Wilson, S. P., Mitchinson, B., Pearson, M., Bednar, J. A. & Prescott, T. J., 1 Jan 2009, In : BMC Neuroscience. 10, Suppl 1, p. P334

    Research output: Contribution to journalArticle

  77. Learning effects of robot actions using temporal associations

    Cohen, P. R., Sutton, C. & Burns, B., 2002, Development and Learning, 2002. Proceedings. The 2nd International Conference on. p. 96-101 6 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  78. Learning encoding and decoding filters for data representation with a spiking neuron

    Gutmann, M., Hyvärinen, A. & Aihara, K., 2008, Proc. Int. Joint Conference on Neural Networks (IJCNN). p. 243-248 6 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  79. Learning features by contrasting natural images with noise

    Gutmann, M. & Hyvärinen, A., 2009, Artificial Neural Networks – ICANN 2009: 19th International Conference, Limassol, Cyprus, September 14-17, 2009, Proceedings, Part II. Alippi, C., Polycarpou, M., Panayiotou, C. & Ellinas, G. (eds.). Springer Berlin Heidelberg, p. 623-632 10 p. (Lecture Notes in Computer Science; vol. 5769).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  80. Learning generative texture models with extended Fields-of-Experts

    Heess, N., Williams, C. K. I. & Hinton, G. E., 2009, Proceedings of the British Machine Vision Conference. BMVA Press, p. 115.1-115.11

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  81. Learning in Markov Random Fields with Contrastive Free Energies

    Welling, M. & Sutton, C., 2005, Tenth International Workshop on Artificial Intelligence and Statistics. 8 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  82. Learning multi-whisker spatial-temporal cortical receptive fields from robotic whisker input

    Bednar, J., Wilson, S. P., Mitchinson, B., Pearson, M. & Prescott, T. J., Oct 2009.

    Research output: Contribution to conferencePoster

  83. Learning reconstruction and prediction of natural stimuli by a population of spiking neurons

    Gutmann, M. & Hyvärinen, A., 2009, 17th European Symposium on Artificial Neural Networks (ESANN). Verleysen, M. (ed.). d-side publications, p. 409-414 6 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  84. Learning structural equation models for fMRI

    Simonotto, E., Whalley, H., Lawrie, S., Murray, L., Mcgonigle, D. & Storkey, A. J., 2006, Advances in Neural Information Processing Systems 19 (NIPS 2006). MIT Press, p. 1329-1336 8 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  85. Learning to find occlusion regions

    Humayun, A., Mac Aodha, O. & Brostow, G. J., 22 Aug 2011, CVPR 2011. Institute of Electrical and Electronics Engineers (IEEE), p. 2161-2168 8 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  86. Learning to segment images using dynamic feature binding

    Mozer, M. C., Zemel, R. S., Behrmann, M. & Williams, C. K. I., Sep 1992, In : Neural Computation. 4, 5, p. 650-665 16 p.

    Research output: Contribution to journalArticle

  87. Learning what to expect (in visual perception)

    Seriès, P. & Seitz, A. R., 24 Oct 2013, In : Frontiers in Human Neuroscience. 7

    Research output: Contribution to journalArticle

  88. Left eye and right eye in reading left-to-right and right-to-left orthographies

    Obregón, M., Kreiner, H. & Shillcock, R., 1 Aug 2013.

    Research output: Contribution to conferencePoster

  89. Lending direction to neural networks

    Zemel, R. S., Williams, C. K. I. & Mozer, M. C., 1995, In : Neural Networks. 8, 4, p. 503-512 10 p.

    Research output: Contribution to journalArticle

Previous 1...3 4 5 6 7 8 9 10 ...14 Next