Edinburgh Research Explorer

Institute for Adaptive and Neural Computation

Organisational unit: Research Institute

  1. Complexity and specificity of experimentally-induced expectations in motion perception

    Chalk, M., Seitz, A. R., Seriès, P. & Gekas, N., Mar 2013, In : Journal of Vision. 13, 4, 8.

    Research output: Contribution to journalArticle

  2. Composite denoising autoencoders

    Geras, K. & Sutton, C., 4 Sep 2016, Machine Learning and Knowledge Discovery in Databases: European Conference on Machine Learning and Knowledge Discovery in Databases ECML PKDD 2016. Springer International Publishing, p. 681-696 16 p. (Lecture Notes in Computer Science (LNCS); vol. 9851).

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

  3. Composition of Conditional Random Fields for Transfer Learning

    Sutton, C. & McCallum, A., 1 Oct 2005, Proceedings of Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing. Vancouver, British Columbia, Canada: Association for Computational Linguistics, p. 748-754 7 p.

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

  4. Computation With Infinite Neural Networks

    Williams, C. K. I., 1 Jul 1997, In : Neural Computation. 10, 5, p. 1203-1216 14 p.

    Research output: Contribution to journalArticle

  5. Computation with populations codes in layered networks of integrate-and-fire neurons

    van Rossum, M. C. W. & Renart, A., 2004, In : Neurocomputing. 58-60, 0, p. 265 - 270

    Research output: Contribution to journalArticle

  6. Computational Maps in the Visual Cortex

    Miikkulainen, R., Bednar, J., Choe, Y. & Sirosh, J., 2005, New York: Springer New York.

    Research output: Book/ReportBook

  7. Computational modelling of memory retention from synapse to behaviour

    van Rossum, M. C. W. & Shippi, M., 12 Mar 2013, In : Journal of Statistical Mechanics: Theory and Experiment. 2013, 03, 13 p., P03007.

    Research output: Contribution to journalArticle

  8. Computers and Octi: Report from the 2001 Tournament

    Sutton, C., Jun 2002, In : ICGA Journal. 25, 2, p. 105-112

    Research output: Contribution to journalArticle

  9. Concurrent Analysis of Neural Activity at Multiple Scales Using Mixed Vine Copulas

    Onken, A. & Panzeri, S., 23 Sep 2016. 1 p.

    Research output: Contribution to conferenceAbstract

  10. Conditional Noise-Contrastive Estimation of Unnormalised Models

    Ceylan, C. & Gutmann, M., 15 Jul 2018, Proceedings of 35th International Conference on Machine Learning (ICML 2018). Dy, J. & Krause, A. (eds.). Stockholmsmässan, Stockholm Sweden: PMLR, Vol. 80. p. 725-733 9 p. (Proceedings of Machine Learning Research; vol. 80).

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

  11. Conditioned Task-set Competition: Neural Mechanisms of Emotional Interference in Depression

    Series, P., Apr 2017, In : Cognitive, Affective & Behavioral Neuroscience. 17, 2, p. 1-21 22 p.

    Research output: Contribution to journalArticle

  12. Confidence-based integrated reweighting model of task-difficulty explains location-based specificity in perceptual learning

    Talluri, B. C., Hung, S., Seitz, A. R. & Seriès, P., 29 Dec 2015, In : Journal of Vision. 15, 10, 12 p., 17.

    Research output: Contribution to journalArticle

  13. Consequences of selecting technology pathways on cumulative carbon dioxide emissions for the United Kingdom Applied Energy

    Roberts, S. H., Foran, B. D., Axon, C. J., Warr, B. S. & Goddard, N., 28 Jun 2018, In : Applied energy. 228, p. 409-425 17 p.

    Research output: Contribution to journalArticle

  14. Consolidation and translation regulation

    Gal-Ben-Ari, S., Kenney, J. W., Ounalla-Saad, H., Taha, E., David, O., Levitan, D., Gildish, I., Panja, D., Pai, B., Wibrand, K., Simpson, T. I., Proud, C. G., Bramham, C. R., Armstrong, J. D. & Rosenblum, K., Sep 2012, In : Learning & Memory. 19, 9, p. 410-22 13 p.

    Research output: Contribution to journalArticle

  15. Constructing Complex Systems Via Activity-Driven Unsupervised Hebbian Self-Organization

    Bednar, J. A., 5 Jun 2014, Growing Adaptive Machines: Combining Development and Learning in Artificial Neural Networks. Kowaliw, T., Bredeche, N. & Doursat, R. (eds.). Springer Berlin Heidelberg, Vol. 557. p. 201-225 25 p. (Growing Adaptive Machines; vol. 557).

    Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)

  16. Constructing Good Learners Using Evolved Pattern Generators

    Valsalam, V., Bednar, J. & Miikkulainen, R., 2005, Proceedings of the 7th Annual Conference on Genetic and Evolutionary Computation. New York, NY, USA: ACM, p. 11-18 8 p. (GECCO '05).

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

  17. Constructing visual function through prenatal and postnatal learning

    Bednar, J. A. & Miikkulainen, R., 2005, Neuroconstructivism, Vol. 2: Perspectives and Prospects. Mareschal, D., Johnson, M. H., Sirois, S., Spratling, M., Thomas, M. S. C. & Westermann, G. (eds.). Oxford University Press, p. 13-37 25 p.

    Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)

  18. Context Embedding Networks

    Kim, K. H., Mac Aodha, O. & Perona, P., 17 Dec 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition. Institute of Electrical and Electronics Engineers (IEEE), p. 8679-8687 9 p.

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

  19. Context Matters: Towards Extracting a Citation’s Context Using Linguistic Features

    Duma, D., Sutton, C. & Klein, E., 2016, JCDL '16 Proceedings of the 16th ACM/IEEE-CS on Joint Conference on Digital Libraries. ACM, p. 201-202 2 p.

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

  20. Continuous Relaxations for Discrete Hamiltonian Monte Carlo

    Zhang, Y., Sutton, C. A., Storkey, A. J. & Ghahramani, Z., 2012, Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012, Lake Tahoe, Nevada, United States. MIT Press, p. 3203-3211 9 p.

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

  21. Continuous Time Particle Filtering for fMRI

    Murray, L. & Storkey, A. J., 2007, Advances in Neural Information Processing Systems 20. Platt, J. C., Koller, D., Singer, Y. & Roweis, S. (eds.). Cambridge, MA: MIT Press, p. 1049-1056 8 p.

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

  22. Continuously tempered Hamiltonian Monte Carlo

    Graham, M. & Storkey, A., 9 Dec 2016.

    Research output: Contribution to conferenceAbstract

  23. Continuously tempered Hamiltonian Monte Carlo

    Graham, M. & Storkey, A., 15 Aug 2017, The Conference on Uncertainty in Artificial Intelligence (UAI 2017). Sydney, Australia, 10 p.

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

  24. Contrast dependency and prior expectations in human speed perception

    Sotiropoulos, G., Seitz, A. R. & Series, P., 2014, In : Vision Research. 97, 0, p. 16-23 8 p.

    Research output: Contribution to journalArticle

  25. Contrast dependent response latency in a spiking neural network

    York, L. C., Oram, M. & van Rossum, M. C. W., 2007.

    Research output: Contribution to conferencePoster

  26. Contribution of LFP dynamics to single-neuron spiking variability in motor cortex during movement execution

    Rule, M., Vargas-Irwin, C., Donoghue, J. P. & Truccolo, W., 22 Jun 2015, In : Frontiers in Systems Neuroscience. 9, 16 p., 89.

    Research output: Contribution to journalArticle

  27. Control of protein concentrations in heterogeneous cell populations

    Vignoni, A., Oyarzún, D. A., Picó, J. & Stan, G. ., 1 Jul 2013, 2013 European Control Conference (ECC). p. 3633-3639 7 p.

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

  28. Control structure and limitations of biochemical networks

    López-Caamal, F., Oyarzún, D. A., Moreno, J. A. & Kalamatianos, D., 1 Jun 2010, Proceedings of the 2010 American Control Conference. p. 6668-6673 6 p.

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

  29. Controlled overexpression of Pax6 in vivo negatively autoregulates the Pax6 locus, causing cell-autonomous defects of late cortical progenitor proliferation with little effect on cortical arealization

    Manuel, M., Georgala, P. A., Carr, C. B., Chanas, S., Kleinjan, D. A., Martynoga, B., Mason, J. O., Molinek, M., Pinson, J., Pratt, T., Quinn, J. C., Simpson, I., Tyas, D. A., van Heyningen, V., West, J. D. & Price, D. J., 2007, In : Development. 134, 3, p. 545-55 11 p.

    Research output: Contribution to journalArticle

  30. Correlated topographic analysis: estimating an ordering of correlated components

    Sasaki, H., Gutmann, M. U., Shouno, H. & Hyvärinen, A., 2013, In : Machine Learning. 92, 2-3, p. 285-317 33 p.

    Research output: Contribution to journalArticle

  31. Correlation Coefficients Are Insufficient for Analyzing Spike Count Dependencies

    Onken, A., Grünewälder, S. & Obermayer, K., 2009, Advances in Neural Information Processing Systems 22. p. 1383-1391 9 p.

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

  32. Correlation based learning from spike timing dependent plasticity

    van Rossum, M. C. W. & Turrigiano, G. G., 2001, In : Neurocomputing. 38 - 40, p. 409 - 415 7 p.

    Research output: Contribution to journalArticle

  33. Cosine transform priors for enhanced decoding of compressed images

    Storkey, A. & Allan, M., 2004, INTELLIGENT DAA ENGINEERING AND AUTOMATED LEARNING IDEAL 2004, PROCEEDINGS. Yang, ZR., Everson, R. & Yin, H. (eds.). BERLIN: Springer-Verlag Berlin Heidelberg, p. 533-539 7 p. (LECTURE NOTES IN COMPUTER SCIENCE; vol. 3177).

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

  34. Covariance Functions

    Rasmussen, C. E. & Williams, C. K. I., Nov 2005, Gaussian Processes for Machine Learning. Rasmussen, C. E. & Williams, C. K. I. (eds.). MIT Press, p. 79-102 24 p. (Adaptive Computation and Machine Learning series).

    Research output: Chapter in Book/Report/Conference proceedingChapter

  35. Covariance-Controlled Adaptive Langevin Thermostat for Large-Scale Bayesian Sampling

    Shang, X., Zhu, Z., Leimkuhler, B. & Storkey, A., 2015, Neural Information Processing Systems (NIPS). 9 p.

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

  36. Cox process representation and inference for stochastic reaction-diffusion processes

    Schnoerr, D., Grima, R. & Sanguinetti, G., 25 May 2016, In : Nature Communications. 7, p. 1-11 11 p., 11729.

    Research output: Contribution to journalArticle

  37. Creating, documenting and sharing network models

    Crook, S. M., Bednar, J. A., Berger, S., Cannon, R., Davison, A. P., Djurfeldt, M., Eppler, J., Kriener, B., Furber, S., Graham, B., Plesser, H. E., Schwabe, L., Smith, L., Steuber, V. & van Albada, S., 2012, In : Network: Computation in Neural Systems. 23, 4, p. 131-149 19 p.

    Research output: Contribution to journalArticle

  38. Cubic-Spline Flows

    Durkan, C., Bekasovs, A., Murray, I. & Papamakarios, G., 15 Jun 2019, First workshop on Invertible Neural Networks and Normalizing Flows: at ICML 2019. 7 p.

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

  39. Cumulative signal transmission in nonlinear reaction-diffusion networks

    Oyarzún, D. A., López-Caamal, F., Garcia, M. R., Middleton, R. H. & Weiße, A. Y., 5 Aug 2013, In : PLoS ONE. 8, 5

    Research output: Contribution to journalArticle

  40. Curvature–driven smoothing: a learning algorithm for feedforward networks

    Bishop, C., 1993, In : IEEE Transactions on Neural Networks. 4, 5, p. 882-884 3 p.

    Research output: Contribution to journalArticle

  41. Curve adaptation effects on high-level facial-expression judgments are predicted to have the same form as low-level aftereffects

    Zhao, C. R. & Bednar, J. A., 2010, In : Perception. 39, EVCP Abstract Supplement, p. 91-91 1 p.

    Research output: Contribution to journalMeeting abstract

  42. CydDC-mediated reductant export in Escherichia coli controls the transcriptional wiring of energy metabolism and combats nitrosative stress

    Holyoake, L. V., Hunt, S., Sanguinetti, G., Cook, G. M., Howard, M. J., Rowe, M. L., Poole, R. K. & Shepherd, M., 15 Mar 2016, In : Biochemical Journal. 473, 6, p. 693-701 9 p.

    Research output: Contribution to journalArticle

  43. DGW: an exploratory data analysis tool for clustering and visualisation of epigenomic marks

    Lukauskas, S., Visintainer, R., Sanguinetti, G. & Schweikert, G., 13 Dec 2016, In : BMC Bioinformatics. 17, 16, 15 p.

    Research output: Contribution to journalArticle

  44. DTs: Dynamic Trees

    Williams, C. KI. & Adams, N. J., 1999, Advances in Neural Information Processing Systems 11 (NIPS 1998). MIT Press, p. 634-640 7 p.

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

  45. Data Cleaning using Probabilistic Models of Integrity Constraints

    Eduardo, S. & Sutton, C., 10 Dec 2016, NIPS 2016 Workshop on Artificial Intelligence for Data Science (AI4DataSci 2016). 3 p.

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

  46. Data Diff: Interpretable, Executable Summaries of Changes in Distributions for Data Wrangling

    Sutton, C., Hobson, T., Geddes, J. & Caruana, R., 19 Jul 2018, Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. London, United Kingdom: ACM, p. 2279-2288 10 p.

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

  47. Data integration for Classification Problems Employing Gaussian Process Priors

    Girolami, M. & Zhong, M., 2007, Advances in Neural Information Processing Systems 19 (NIPS 2006). MIT Press, 8 p.

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

  48. Data-Intensive Research Workshop (15-19 March 2010) Report

    Atkinson, M., Roure, D. D., van Hemert, J., Jha, S., McNally, R., Mann, R., Viglas, S. & Williams, C. K. I., 1 May 2010, University of Edinburgh. 88 p.

    Research output: Book/ReportOther report

  49. Data-driven statistical learning of temporal logic properties

    Bartocci, E., Bortolussi, L. & Sanguinetti, G., 2014, Formal Modeling and Analysis of Timed Systems: 12th International Conference, FORMATS 2014, Florence, Italy, September 8-10, 2014. Proceedings. Springer International Publishing, p. 23-37 15 p. (Lecture Notes in Computer Science; vol. 8711).

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

  50. Dataset Issues in Object Recognition

    Ponce, J., Berg, T. L., Everingham, M., Forsyth, D. A., Hebert, M., Lazebnik, S., Marszalek, M., Schmid, C., Russell, B. C., Torralba, A., Williams, C. K. I., Zhang, J. & Zisserman, A., 2006, Toward Category-Level Object Recognition. Ponce, J., Hebert, M., Schmid, C. & Zisserman, A. (eds.). Springer Berlin Heidelberg, p. 29-48 20 p. (Lecture Notes in Computer Science; vol. 4170).

    Research output: Chapter in Book/Report/Conference proceedingChapter

  51. Dataset Shift in Machine Learning

    Shimodaira, H., Sugiyama, M., Storkey, A., Gretton, A., David, S-B., QuinoneroCandela, J., Sugiyama, M., Schwaighofer, A. & Lawrence, ND., 2009, DATASET SHIFT IN MACHINE LEARNING. CAMBRIDGE: Yale University Press in association with the Museum of London, p. 201-205 5 p. (Neural Information Processing Series).

    Research output: Chapter in Book/Report/Conference proceedingForeword/postscript

  52. Deep Architectures for Articulatory Inversion

    Uria, B., Murray, I., Renals, S. & Richmond, K., Sep 2012, INTERSPEECH 2012 13th Annual Conference of the International Speech Communication Association. ISCA, p. 867-870 4 p.

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

  53. Deep Dungeons and Dragons: Learning Character-Action Interactions from Role-Playing Game Transcripts

    Louis, A. & Sutton, C., 6 Jun 2018, The 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. New Orleans, Louisiana : Association for Computational Linguistics, p. 708-713 6 p.

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

  54. Deep multimodal autoencoders for identifying latent representations of spike counts and local field potentials

    Onken, A., Yague, J. & Sakata, S., 27 Sep 2018.

    Research output: Contribution to conferencePoster

  55. Dendritic Spine Dynamics Regulate the Long-Term Stability of Synaptic Plasticity

    O'Donnell, C., Nolan, M. & Van Rossum, M., 9 Nov 2011, In : Journal of Neuroscience. 31, 45, p. 16142-16156 15 p.

    Research output: Contribution to journalArticle

  56. Dendritic spines as devices for synaptic metaplasticity

    O'Donnell, C., Nolan, M. & van Rossum, M. C. W., 2009.

    Research output: Contribution to conferencePoster

  57. Dendritic spines can stabilize synaptic weights

    O'Donnell, C., Nolan, M. & van Rossum, M. C. W., 2010.

    Research output: Contribution to conferencePoster

  58. Density of states of disordered systems

    van Rossum, M., Nieuwenhuizen, T. M., Hofstetter, E. & Schreiber, M., 1 May 1994, In : Physical Review B: Condensed Matter and Materials Physics. 49, p. 13377-13382 6 p.

    Research output: Contribution to journalArticle

  59. Derivative processes for modelling metabolic fluxes

    Žurauskiene, J., Kirk, P., Thorne, T., Pinney, J. & Stumpf, M., 1 Jul 2014, In : Bioinformatics. 30, 13, p. 1892-1898 7 p.

    Research output: Contribution to journalArticle

  60. Design constraints in an operon circuit for engineered control of metabolic networks

    Oyarzún, D. A. & Stan, G., 1 Dec 2012, 2012 IEEE 51st IEEE Conference on Decision and Control (CDC). p. 3608-3613 6 p.

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

  61. Design of a bistable switch to control cellular uptake

    Oyarzun, D. & Madalena, C., 6 Dec 2015, In : Journal of the Royal Society Interface. 12, 113, 15 p., 20150618.

    Research output: Contribution to journalArticle

  62. Design of the TRONCO BioConductor Package for TRanslational ONCOlogy

    Antoniotti, M., Caravagna, G., De Sano, L., Graudenzi, A., Mauri, G., Mishra, B. & Ramazzotti, D., 21 Oct 2016, In : The R Journal. 8, 2, p. 39-59 21 p.

    Research output: Contribution to journalArticle

  63. Design tradeoffs in a synthetic gene control circuit for metabolic networks

    Oyarzún, D. A. & Stan, G., 1 Jun 2012, 2012 American Control Conference (ACC). p. 2743-2748 6 p.

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

  64. Detecting Artifactual Events in Vital Signs Monitoring Data

    Lal, P., Williams, C. K. I., Georgatzis, K., Hawthorne, C., McMonagle, P., Piper, I. & Shaw, M., Oct 2016, Machine Learning for Healthcare Technologies. Clifton, D. A. (ed.). IET, p. 7-32 26 p.

    Research output: Chapter in Book/Report/Conference proceedingChapter

  65. Detecting and Quantifying Topographic Order in the Brain

    Yarrow, S., Razak, K., Seitz, A. R. & Series, P., 2013.

    Research output: Contribution to conferencePoster

  66. Detecting and Quantifying Topography in Neural Maps

    Yarrow, S., Seitz, A. R., Seriès, P. & Razak, K., 5 Feb 2014, In : PLoS Neglected Tropical Diseases. 9, 2, 14 p., e87178.

    Research output: Contribution to journalArticle

  67. Detecting and reconstructing vascular trees in retinal images

    Jasiobedzki, P., Williams, C. K. I. & Lu, F., 1994, Proc. SPIE 2167, Medical Imaging 1994: Image Processing. p. 815-825 11 p.

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

  68. Detecting repeated cancer evolution from multi-region tumor sequencing data

    Caravagna, G., Giarratano, Y., Ramazzotti, D., Tomlinson, I., Graham, T. A., Sanguinetti, G. & Sottoriva, A., 31 Aug 2018, In : Nature Methods. 15, p. 707-714 8 p.

    Research output: Contribution to journalArticle

  69. Detection of Substructure in Receptive Fields of Retinal Ganglion Cells

    Onken, A., Liu, J. K., Delis, I., Panzeri, S. & Gollisch, T., 5 Sep 2014. 1 p.

    Research output: Contribution to conferenceAbstract

  70. Determining heat use in residential buildings using high resolution gas and domestic hot water monitoring

    Buswell, R. A., Marini, D., Webb, L. & Thomson, M., 2013, Proceedings of the 13th Conference of International Building Performance Simulation Association. Chambéry, France: International Building Performance Simulation Association, p. 2413-2420 8 p.

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

  71. Determining synaptic input properties from intra-cellular recordings in vivo

    Pelko, M., Puggioni, P., Van Rossum, M. & Bouscein, C., 2012.

    Research output: Contribution to conferencePoster

  72. Developing Complex Systems Using Evolved Pattern Generators

    Valsalam, V. K., Bednar, J. A. & Miikkulainen, R., 2007, In : IEEE Transactions on Evolutionary Computation. p. 181-198 18 p.

    Research output: Contribution to journalArticle

  73. Developing maps of complex cells in a computational model

    Antolik, J. & Bednar, J., 13 Jul 2008.

    Research output: Contribution to conferencePoster

  74. Developing maps of complex cells in a computational model of V1

    Antolik, J. & Bednar, J., 19 Nov 2008.

    Research output: Contribution to conferencePoster

  75. Developing the Technology for a Shared Demand Responsive Transport System at the University of Malta

    Attard, M., Muscat, A. & Camilleri, M., 8 Jan 2018.

    Research output: Contribution to conferencePaper

  76. Development of maps of simple and complex cells in the primary visual cortex

    Antolik, J. & Bednar, J. A., 2011, In : Frontiers in Computational Neuroscience. 5, 17

    Research output: Contribution to journalArticle

  77. Development of the ASHRAE Global Thermal Comfort Database II

    Földváry, V., Cheung, T., Zhang, H., de Dear, R., Parkinson, T., Arens, E., Chun, C., Schiavon, S., Luo, M., Brager, G., Li, P., Kaam, S., Adebamowo, M. A., Andamon, M. M., Babich, F., Bouden, C., Bukovianska, H., Candido, C., Cao, B., Carlucci, S. & 44 others, Cheong, D. K. W., Choi, J-H., Cook, M., Cropper, P., Deuble, M., Heidari, S., Indraganti, M., Jin, Q., Kim, H., Kim, J., Konis, K., Singh, M. K., Kwok, A., Lamberts, R., Loveday, D., Langevin, J., Manu, S., Moosmann, C., Nicol, F., Ooka, R., Oseland, N. A., Pagliano, L., Petráš, D., Rawal, R., Romero, R., Sekhar, C., Schweiker, M., Tartarini, F., Tanabe, S., Tham, K. W., Teli, D., Toftum, J., Toledo, L., Tsuzuki, K., De Vecchi, R., Wagner, A., Wang, Z., Wallbaum, H., Webb, L., Yang, L., Zhu, Y., Zhai, Y., Zhang, Y. & Zhou, X., Sep 2018, In : Building and Environment. 142, p. 502-512 11 p.

    Research output: Contribution to journalArticle

  78. Developmental Profiles of Eczema, Wheeze, and Rhinitis: Two Population-Based Birth Cohort Studies

    Belgrave, D. C. M., Granell, R., Simpson, A., Guiver, J., Bishop, C., Buchan, I. E., Henderson, J. & Custovic, A., 1 Oct 2014, In : PLoS ONE. 11, 10, 14 p., e1001748.

    Research output: Contribution to journalArticle

  79. Developmental organization of central neurons in the adult Drosophila ventral nervous system

    Shepherd, D., Sahota, V., Court, R., Williams, D. W. & Truman, J. W., 15 Oct 2019, In : Journal of Comparative Neurology. 527, 15, p. 2573-2598 72 p.

    Research output: Contribution to journalArticle

  80. Developments of the generative topographic mapping

    Bishop, C. M., Svensén, M. & Williams, C. K. I., Nov 1998, In : Neurocomputing. 21, 1–3, p. 203-224 22 p.

    Research output: Contribution to journalArticle

  81. Deviations from the Gaussian distribution of mesoscopic conductance fluctuations

    van Rossum, M., Lerner, I. V., Altshuler, B. L. & Nieuwenhuizen, T. M., 1 Feb 1997, In : Physical Review B. 55, p. 4710-4716 7 p.

    Research output: Contribution to journalArticle

  82. Dictionary of Computer Vision and Image Processing, 2nd Edition

    Fisher, B., Breckon, T. P., Dawson-Howe, K., Fitzgibbon, A., Roberston, C., Trucco, E. & Williams, C. K. I., Dec 2013, 2 ed. Wiley. 384 p.

    Research output: Book/ReportBook

  83. Dietary Salt Levels Affect Salt Preference and Learning in Larval Drosophila

    Russell, C., Wessnitzer, J., Young, J. M., Armstrong, J. D. & Webb, B., 1 Jun 2011, In : PLoS ONE. 6, 6, 8 p., e20100.

    Research output: Contribution to journalArticle

  84. Differences of split and non-split architectures emerged from modelling Chinese character pronunciation

    Hsiao, J. H. & Shillcock, R., 2005, Proceedings of the Twenty Seventh Annual Conference of the Cognitive Science Society. p. 989-994 6 p.

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

  85. Different binocular foveal strategies in reading: younger and older readers

    Paul, S. A., Obregón, M. & Shillcock, R., 1 Aug 2013.

    Research output: Contribution to conferencePoster

  86. Differential vergence movements in reading Chinese and English: Greater fixation-initial binocular disparity is advantageous in reading the denser orthography

    Hsiao, Y., Shillcock, R., Obregón, M., Kreiner, H., Roberts, M. A. J. & McDonald, S., 11 Jul 2017, In : Quarterly Journal of Experimental Psychology. p. 1-33 33 p.

    Research output: Contribution to journalArticle

  87. Digging Into Self-Supervised Monocular Depth Estimation

    Godard, C., Mac Aodha, O., Firman, M. & Brostow, G. J., 27 Feb 2020, 2019 IEEE/CVF International Conference on Computer Vision (ICCV). Institute of Electrical and Electronics Engineers (IEEE), p. 3827-3837 11 p.

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

  88. Direct Learning of Sparse Changes in Markov Networks by Density Ratio Estimation

    Liu, S., Quinn, J. A., Gutmann, M. U., Suzuki, T. & Sugiyama, M., 1 Mar 2014, In : Neural Computation. 26, 6, p. 1169-1197 29 p.

    Research output: Contribution to journalArticle

  89. Direct Learning of Sparse Changes in Markov Networks by Density Ratio Estimation

    Liu, S., Quinn, J. A., Gutmann, M. U. & Sugiyama, M., Sep 2013, Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2013, Prague, Czech Republic, September 23-27, 2013, Proceedings, Part II. Springer Berlin Heidelberg, p. 596-611 16 p. (Lecture Notes in Computer Science; vol. 8189).

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

  90. Directional-unit boltzmann machines

    Zemel, R. S., Williams, C. K. I. & Mozer, M. C., 1993, Advances in Neural Information Processing Systems 5. Morgan Kaufmann Publishers Inc., p. 172-179 8 p.

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

  91. Disciplinary Differences in Blended Learning Design: A Network Analytic Study

    Whitelock-Wainwright, A., Tsai, Y-S., Lyons, K., Khalif, S., Bryant, M., Ryan, K. & Gasevic, D., 23 Mar 2020, LAK '20: Proceedings of the Tenth International Conference on Learning Analytics & Knowledge. Association for Computing Machinery (ACM), p. 579-588 10 p.

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

  92. Discovering hidden features with Gaussian processes regression

    Vivarelli, F. & Williams, C. K. I., 1999, Advances in Neural Information Processing Systems 11 (NIPS 1998). MIT Press, p. 613-619 7 p.

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

  93. Discriminative Mixtures of Sparse Latent Fields for Risk Management

    Agakov, F. V., Orchard, P. & Storkey, A. J., 2012, Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics (AISTATS-12). Lawrence, N. D. & Girolami, M. A. (eds.). Vol. 22. p. 10-18 9 p.

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

  94. Discriminative Switching Linear Dynamical Systems applied to Physiological Condition Monitoring

    Georgatzis, K. & Williams, C. K. I., 2015, 31st Conference on Uncertainty in Artificial Intelligence (UAI 2015). 10 p. 77

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

Previous 1 2 3 4 5 6 7 8 ...14 Next