Edinburgh Research Explorer

Institute for Adaptive and Neural Computation

Organisational unit: Research Institute

  1. Classification of Elbow Electormyography Signals based on Directed Transfer Functions

    Latif, R., Sanei, S. & Nazarpour, K., 24 Jun 2008, 2008 International Conference on BioMedical Engineering and Informatics. Institute of Electrical and Electronics Engineers (IEEE), p. 371-374 4 p.

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

  2. Classification of arterial plaque by spectral analysis of in vitro radio frequency intravascular ultrasound data

    Watson, R. J., McLean, C. C., Moore, M. P., Spencer, T., Salter, D. M., Anderson, T., Fox, K. A. A. & McDicken, W. N., Jan 2000, In : Ultrasound in Medicine & Biology. 26, 1, p. 73-80 8 p.

    Research output: Contribution to journalArticle

  3. Classifying chemical mode of action using gene networks and machine learning: A case study with the herbicide linuron

    Ornostay, A., Cowie, A. M., Hindle, M., Baker, C. J. O. & Martyniuk, C. J., 12 Sep 2013, In : Comparative Biochemistry and Physiology - Part D: Genomics and Proteomics. 8, 4, p. 263-274 12 p.

    Research output: Contribution to journalArticle

  4. Cleaning astronomical databases using hough transforms and renewal strings

    Williams, CKI., Storkey, AJ., Hambly, NC. & Mann, RG., 2004, Advances in Scattering and Biomedical Engineering: Proceedings of the Sixth International Workshop. Fotiadis, DI. & Massalas, CV. (eds.). World Scientific, p. 439-452 14 p.

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

  5. Cleaning sky survey databases using Hough transform and renewal string approaches

    Storkey, AJ., Hambly, NC., Williams, CKI. & Mann, RG., 1 Jan 2004, In : Monthly Notices of the Royal Astronomical Society. 347, 1, p. 36-51 16 p.

    Research output: Contribution to journalArticle

  6. Clinical characteristics of children and young people admitted to hospital with covid-19 in United Kingdom: prospective multicentre observational cohort study

    Swann, O. V., Holden, K. A., Turtle, L., Pollock, L., Fairfield, C. J., Drake, T. M., Seth, S., Egan, C., Hardwick, H. E., Halpin, S., Girvan, M., Donohue, C., Pritchard, M., Patel, L. B., Ladhani, S., Sigfrid, L., Sinha, I. P., Olliaro, P. L., Nguyen-van-tam, J. S., Horby, P. W. & 8 others, Merson, L., Carson, G., Dunning, J., Openshaw, P. J. M., Baillie, J. K., Harrison, E. M., Docherty, A. B. & Semple, M. G., 27 Aug 2020, In : British Medical Journal (BMJ). p. m3249

    Research output: Contribution to journalArticle

  7. Clumps, Clusters and Classification

    Bishop, C., 2004, Computer Systems: Theory, Technology, and Applications. Herbert, A. & Jones, K. (eds.). Springer New York, p. 39-49 11 p. (Monographs in Computer Science).

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

  8. Clustered Coding Variants in the Glutamate Receptor Complexes of Individuals with Schizophrenia and Bipolar Disorder

    Frank, R. A. W., McRae, A. F., Pocklington, A. J., Van De Lagemaat, L., Navarro, P., Croning, M. D. R., Komiyama, N. H., Bradley, S. J., Challiss, R. A. J., Armstrong, J. D., Finn, R. D., Malloy, M. P., MacLean, A. W., Harris, S. E., Starr, J., Bhaskar, S. S., Howard, E. K., Hunt, S. E., Coffey, A. J., Ranganath, V. & 7 others, Deloukas, P., Rogers, J., Muir, W. J., Deary, I. J., Blackwood, D. H., Visscher, P. M. & Grant, S. G. N., 29 Apr 2011, In : PLoS ONE. 6, 4, p. - 9 p., e19011.

    Research output: Contribution to journalArticle

  9. Clustering with a Reject Option: Interactive Clustering as Bayesian Prior Elicitation

    Srivastava, A., Zou, J. & Sutton, C., 27 Jul 2016, Proceedings of the 2016 ICML Workshop on Human Interpretability in Machine Learning (WHI 2016). p. 16-20 5 p.

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

  10. Co-Designing Innovations for Energy Saving in Large Organisations

    Morgan, E., Webb, L., Goddard, N., Carter, C. & Webb, J., 14 Jun 2017, DIS '17 Companion Proceedings of the 2017 ACM Conference Companion Publication on Designing Interactive Systems. ACM, p. 50-54 5 p.

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

  11. Co-Designing a Device for Behaviour-Based Energy Reduction in a Large Organisation

    Morgan, E., Webb, L., Carter, K. & Goddard, N., 1 Nov 2018, In : Proceedings of the ACM on Human-Computer Interaction. 2, CSCW, 23 p., 125.

    Research output: Contribution to journalArticle

  12. CoGNaC: A Chaste Plugin for the Multiscale Simulation of Gene Regulatory Networks Driving the Spatial Dynamics of Tissues and Cancer

    Rubinacci, S., Graudenzi, A., Caravagna, G., Mauri, G., Osborne, J., Pitt-Francis, J. & Antoniotti, M., 1 Sep 2015, In : Cancer Informatics. p. 53-65 13 p.

    Research output: Contribution to journalArticle

  13. ColNet: Embedding the Semantics of Web Tables for Column Type Prediction

    Chen, J., Jiménez-Ruiz, E., Horrocks, I. & Sutton, C., 23 Jul 2019, Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19): Thirty-First Conference on Innovative Applications of Artificial Intelligence The Ninth Symposium on Educational Advances in Artificial Intelligence - AAAI Technical Track: AI and the Web. Honolulu, Hawaii, United States: AAAI Press, Vol. 33. p. 29-36 8 p. (Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence).

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

  14. Collective Segmentation and Labeling of Distant Entities in Information Extraction

    Sutton, C. & McCallum, A., 2004, ICML Workshop on Statistical Relational Learning and Its Connections to Other Fields. 7 p.

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

  15. Combinatorial stresses kill pathogenic Candida species

    Kaloriti, D., Tillmann, A., Cook, E., Jacobsen, M., You, T., Lenardon, M., Ames, L., Barahona, M., Chandrasekaran, K., Coghill, G., Goodman, D., Gow, N. A. R., Grebogi, C., Ho, H. L., Ingram, P., McDonagh, A., De Moura, A. P. S., Pang, W., Puttnam, M., Radmaneshfar, E. & 10 others, Romano, M. C., Silk, D., Stark, J., Stumpf, M., Thiel, M., Thorne, T., Usher, J., Yin, Z., Haynes, K. & Brown, A. J. P., 1 Oct 2012, In : Medical Mycology. 50, 7, p. 699-709 11 p.

    Research output: Contribution to journalArticle

  16. Combined influence of forearm orientation and muscular contraction on EMG pattern recognition

    Khushaba, R. N., Al-Timemy, A., Kodagoda, S. & Nazarpour, K., 1 Nov 2016, In : Expert Systems with Applications. 61, p. 154-161 8 p.

    Research output: Contribution to journalArticle

  17. Combining belief networks and neural networks for scene segmentation

    Feng, X., Williams, C. K. I. & Felderhof, S. N., 1 Apr 2002, In : IEEE Transactions on Pattern Analysis and Machine Intelligence. 24, 4, p. 467-483 17 p.

    Research output: Contribution to journalArticle

  18. Combining neural networks and belief networks for image segmentation

    Williams, C. K. I. & Feng, X., 1 Aug 1998, Neural Networks for Signal Processing VIII, 1998. Proceedings of the 1998 IEEE Signal Processing Society Workshop. Institute of Electrical and Electronics Engineers (IEEE), p. 393-401 9 p.

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

  19. Combining tree-based and dynamical systems for the inference of gene regulatory networks

    Huynh-Thu, V. A. & Sanguinetti, G., 15 May 2015, In : Bioinformatics. 31, 10, p. 1614-1622 9 p.

    Research output: Contribution to journalArticle

  20. Combining two methods of recognizing hand-printed digits

    E. Hinton, G., Williams, C. K. I. & Revow, M. D., 1992, In : Artificial Neural Networks. 2, p. 53-60 8 p.

    Research output: Contribution to journalArticle

  21. Compact Explanations of Why Malware is Bad

    Chen, W., Sutton, C., Gordon, A., Aspinall, D., Muttik, I. & Shen, Q., 10 Aug 2015, (Accepted/In press) AI4FM 2015. 4 p.

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

  22. Comparing Bayesian Neural Network Algorithms for Classifying Segmented Outdoor Images

    Vivarelli, F. & Williams, C. K. I., 1 May 2001, In : Neural Networks. 14, 4-5, p. 427-437 11 p.

    Research output: Contribution to journalArticle

  23. Comparing Mean Field and Exact EM in Tree Structured Belief Networks

    Adams, N. J., Williams, C. K. I. & Storkey, A. J., 2001, In Fourth International ICSC Symposium on Soft Computing and Intelligent Systems for Industry. ICSC-NAISO Adademic. Thoemmes Press, 6 p.

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

  24. Comparing Probabilistic Models for Melodic Sequences

    Spiliopoulou, A. & Storkey, A., 2011, MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES, PT III. Gunopulos, D., Hofmann, T., Malerba, D. & Vazirgiannis, M. (eds.). BERLIN: Springer-Verlag Berlin Heidelberg, p. 289-304 16 p. (Lecture Notes in Artificial Intelligence; vol. 6913).

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

  25. Comparison of Generative and Discriminative Techniques for Object Detection and Classification

    Ulusoy, I. & Bishop, C., 2006, Toward Category-Level Object Recognition. Ponce, J., Hebert, M., Schmid, C. & Zisserman, A. (eds.). Springer Berlin Heidelberg, p. 173-195 23 p. (Lecture Notes in Computer Science; vol. 4170).

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

  26. Comparison of different moment-closure approximations for stochastic chemical kinetics

    Schnoerr, D., Sanguinetti, G. & Grima, R., 14 Nov 2015, In : The Journal of Chemical Physics. 143, 18, 17 p., 185101.

    Research output: Contribution to journalArticle

  27. Comparison of hand and forearm muscle pairs in controlling of a novel myoelectric interface

    Barnes, J., Dyson, M. & Nazarpour, K., 9 Feb 2017, 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC). Institute of Electrical and Electronics Engineers (IEEE), p. 002846-002849 4 p.

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

  28. Compensations for Diminished Terminal Oxidase Activity in Escherichia coli: Cytochrome bd-II-Mediated Respiration and Glutamate Metabolism

    Shepherd, M., Sanguinetti, G., Cook, G. M. & Poole, R. K., 11 Jun 2010, In : Journal of Biological Chemistry. 285, 24, p. 18464-18472 9 p.

    Research output: Contribution to journalArticle

  29. Compiling and Optimizing for Decoupled Architectures

    Topham, N., Rawsthorne, A., McLean, C., Mewissen, M. & Bird, P., 1995, Supercomputing, 1995. Proceedings of the IEEE/ACM SC95 Conference. Institute of Electrical and Electronics Engineers (IEEE), p. 40-40 1 p.

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

  30. Complex-Valued Independent Component Analysis of Natural Images

    Laparra, V., Gutmann, M. U., Malo, J. & Hyvärinen, A., 2011, Artificial Neural Networks and Machine Learning -- ICANN 2011: 21st International Conference on Artificial Neural Networks, Espoo, Finland, June 14-17, 2011, Proceedings, Part II. Honkela, T., Duch, W., Girolami, M. & Kaski, S. (eds.). Berlin, Heidelberg: Springer Berlin Heidelberg, p. 213-220 8 p. (Lecture Notes in Computer Science; vol. 6792).

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

  31. Complexity Leadership in Learning Analytics: Drivers, Challenges, and Opportunities

    Tsai, Y-S., Poquet, O., Gašević, D., Dawson, S. & Pardo, A., 21 Oct 2019, In : British Journal of Educational Technology. 50, 6, p. 2839–2854

    Research output: Contribution to journalArticle

  32. Complexity and specificity of experimentally induced expectations in motion perception

    Gekas, N., Chalk, M., Seitz, A. R. & Seriès, P., 1 Jan 2013, p. 355. 1 p.

    Research output: Contribution to conferencePoster

  33. 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

  34. 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

  35. 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

  36. 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

  37. 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

  38. Computational Maps in the Visual Cortex

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

    Research output: Book/ReportBook

  39. Computational Psychiatry: A Primer

    Series, P. (ed.), 1 Nov 2020, MIT Press. 342 p.

    Research output: Book/ReportBook

  40. 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

  41. 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

  42. 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

  43. 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

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

    Stolicyn, A., Steele, D. & Series, P., 1 Apr 2017, In : Cognitive, Affective & Behavioral Neuroscience. 17, 2, p. 269–289 21 p.

    Research output: Contribution to journalArticle

  45. 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

  46. 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

  47. 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

  48. 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)

  49. 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

  50. 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)

  51. 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

  52. 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

  53. Context-Based Object Recognition: Indoor Versus Outdoor Environments

    Alameer, A., Degenaar, P. & Nazarpour, K., 24 Apr 2019, Advances in Computer Vision. Arai, K. & Kapoor, S. (eds.). Cham: Springer International Publishing AG, p. 473-490 18 p. (Advances in Intelligent Systems and Computing; vol. 944).

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

  54. 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

  55. 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

  56. Continuous Versus Discrete Simultaneous Control of Prosthetic Fingers

    Krasoulis, A., Vijayakumar, S. & Nazarpour, K., 29 Oct 2018, Proceedings of the 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). Honolulu, HI, USA: Institute of Electrical and Electronics Engineers (IEEE), p. 3774-3777 4 p.

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

  57. Continuously tempered Hamiltonian Monte Carlo

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

    Research output: Contribution to conferenceAbstract

  58. 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

  59. 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

  60. 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

  61. 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

  62. 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

  63. 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

  64. 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

  65. 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

  66. 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

  67. 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

  68. 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

  69. 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

  70. 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

  71. 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

  72. 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

  73. 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

  74. 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

  75. 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

  76. 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

  77. 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

  78. 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

  79. 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

  80. 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

  81. 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

  82. Data Driven Spatial Filtering Can Enhance Abstract Myoelectric Control in Amputees

    Dyson, M. & Nazarpour, K., 29 Oct 2018, 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). Institute of Electrical and Electronics Engineers (IEEE), p. 3770-3773 4 p.

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

  83. 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

  84. 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

  85. 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

  86. 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

  87. 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

  88. Dealing with Ambiguity in Robotic Grasping via Multiple Predictions

    Ghazaei, G., Laina, I., Rupprecht, C., Tombari, F., Navab, N. & Nazarpour, K., 25 May 2019, Computer Vision -- ACCV 2018. Jawahar, C. V., Li, H., Mori, G. & Schindler, K. (eds.). Cham: Springer International Publishing, p. 38-55 18 p. (Lecture Notes in Computer Science ; vol. 11364).

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

  89. 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

  90. 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

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