Edinburgh Research Explorer

Institute for Adaptive and Neural Computation

Organisational unit: Research Institute

  1. Activity Deprivation Reduces Miniature IPSC Amplitude by Decreasing the Number of Postsynaptic GABAA Receptors Clustered at Neocortical Synapses

    Kilman, V. L., van Rossum, M. C. W. & Turrigiano, G. G., 15 Feb 2002, In : The Journal of Neuroscience. 22, 4, p. 1328-1337 10 p.

    Research output: Contribution to journalArticle

  2. Activity coregulates quantal AMPA and NMDA currents at neocortical synapses

    Watt, A. J., van Rossum, M. C. W., MacLeod, K. M., Nelson, S. B. & Turrigiano, G. G., Jun 2000, In : Neuron. 26, 3, p. 659-670 12 p.

    Research output: Contribution to journalArticle

  3. Adaptable Pouring: Teaching Robots Not to Spill using Fast but Approximate Fluid Simulation

    Lopez Guevara, T., Gutmann, M., Ramamoorthy, S., taylor, N. & Subr, K., 31 Oct 2017, The 1st Annual Conference on Robot Learning (CoRL 2017). Zurich, Switzerland, Vol. 78. p. 77-86 10 p.

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

  4. Adaptation of anaerobic cultures of Escherichia coli K-12 in response to environmental trimethylamine-N-oxide

    Denby, K. J., Rolfe, M. D., Crick, E., Sanguinetti, G., Poole, R. K. & Green, J., Jul 2015, In : Environmental Microbiology. 17, 7, p. 2477-2491 15 p.

    Research output: Contribution to journalArticle

  5. Adaptive Gaussian Copula ABC

    Chen, Y. & Gutmann, M., 25 Apr 2019, Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics (AISTATS 2019). Naha, Okinawa, Japan: PMLR, Vol. 89. p. 1584-1592 14 p.

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

  6. Adaptive Stochastic Primal-Dual Coordinate Descent for Separable Saddle Point Problems

    Zhu, Z. & Storkey, A., 2015, Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2015, Porto, Portugal, September 7-11, 2015, Proceedings, Part I. Appice, A., Rodrigues, P. P., Santos Costa, V., Soares, C., Gama, J. & Jorge, A. (eds.). Springer International Publishing, p. 645-658 14 p. (Lecture Notes in Computer Science; vol. 9284).

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

  7. Adaptive elastic models for hand-printed character recognition

    Hinton, G. E., Williams, C. K. I. & Revow, M. D., 1991, Advances in Neural Information Processing Systems 4 (NIPS 1991). MIT Press, p. 512-519 8 p.

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

  8. Adaptive integration in the visual cortex by depressing recurrent cortical circuits

    van Rossum, M. C. W., van der Meer, M., Xiao, D. K. & Oram, M. W., Jul 2008, In : Neural Computation. 20, 7, p. 1847-1872 26 p.

    Research output: Contribution to journalArticle

  9. Adaptive thresholding for reliable topological inference in single subject fMRI analysis

    Gorgolewski, K. J., Storkey, A. J., Bastin, M. E. & Pernet, C. R., 25 Aug 2012, In : Frontiers in Human Neuroscience. 6, 245.

    Research output: Contribution to journalArticle

  10. Adding Constrained Discontinuities to Gaussian Process Models of Wind Fields

    Cornford, D., Nabney, I. T. & Williams, C. K. I., 1998, Advances in Neural Information Processing Systems 11 (NIPS 1998). p. 861-867 7 p.

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

  11. Age-dependent Homeostatic Plasticity of GABAergic Signaling in Developing Retinal Networks

    Hennig, M., Grady, J., van Coppenhagen, J. & Sernagor, E., 24 Aug 2011, In : The Journal of Neuroscience. 31, 34, p. 12159-12164 6 p.

    Research output: Contribution to journalArticle

  12. Aggregation Under Bias: Rényi Divergence Aggregation and Its Implementation via Machine Learning Markets

    Storkey, A. J., Zhu, Z. & Hu, J., 2015, Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2015, Porto, Portugal, September 7-11, 2015, Proceedings, Part I. Appice, A., Rodrigues, P. P., Santos Costa, V., Soares, C., Gama, J. & Jorge, A. (eds.). Springer International Publishing, p. 560-574 15 p. (Lecture Notes in Computer Science; vol. 9284).

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

  13. Algorithmic methods to infer the evolutionary trajectories in cancer progression

    Caravagna, G., Graudenzi, A., Ramazzotti, D., Sanz-Pamplona, R., De Sano, L., Mauri, G., Moreno, V., Antoniotti, M. & Mishra, B., 12 Jul 2016, In : Proceedings of the National Academy of Sciences. 113, 28, p. E4025-E4034 10 p.

    Research output: Contribution to journalArticle

  14. Amortized Inference for Latent Feature Models Using Variational Russian Roulette

    Xu, K., Srivastava, A. & Sutton, C., 2018. 11 p.

    Research output: Contribution to conferencePaper

  15. An EM Algorithm for Independent Component Analysis in the Presence of Gaussian Noise

    Zhong, M., Tang, H., Wang, H. & Tang, Y., Jan 2004, In : Neural Information Processing - Letters and Reviews. p. 11-17 7 p.

    Research output: Contribution to journalArticle

  16. An Experimental Research Design for Evaluating Energy Feedback

    Pullinger, M., Goddard, N. & Webb, J., 9 Sep 2016, The 4th European Conference on Behaviour and Energy Efficiency (Behave 2016). 12 p.

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

  17. An Introduction to Conditional Random Fields

    Sutton, C. & McCallum, A., 2012, In : Foundations and Trends in Machine Learning. 4, 4, p. 267-373 109 p.

    Research output: Contribution to journalArticle

  18. An Introduction to Conditional Random Fields for Relational Learning

    Sutton, C. & McCallum, A., 2007, Introduction to Statistical Relational Learning. MIT Press, p. 93-128 36 p.

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

  19. An Investigation of Coupled Energy and Particle Transport

    Bishop, C. M., Connor, J. W., Cox, M., Deliyankis, N. & Robinson, D. C., 1994, Proceedings 17th European Physical Society on Controlled Fusion and Plasma Heating,. Vol. 1. p. 178-178 178 p.

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

  20. An Upper Bound on the Bayesian Error Bars for Generalized Linear Regression

    Qazaz, C. S., Williams, C. K. I. & Bishop, C. M., 1997, Mathematics of Neural Networks: Models, Algorithms and Applications. Norwell, MA, USA: Springer US, p. 295-299 5 p. (Operations Research/Computer Science Interfaces Series; vol. 8).

    Research output: Chapter in Book/Report/Conference proceedingChapter

  21. An analytic characterization of a stabilizing feedback for LTI plants

    Peters, A. A., Oyarzun, D. A., Silva, E. I. & Salgado, M. E., 2 Apr 2015, 2009 European Control Conference, ECC 2009. IEEE, p. 231-235 5 p. 7074409

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

  22. An anatomically-unbiased approach for analysis of renal BOLD magnetic resonance images

    Menzies, R., Zammit-Mangion, A., Hollis, L. M., Lennen, R. J., Jansen, M. A., Webb, D. J., Mullins, J. J., Dear, J., Sanguinetti, G. & Bailey, M. A., 17 Jul 2013, In : American Journal of Physiology-Renal Physiology. 305, p. F845-F852 n/a.

    Research output: Contribution to journalArticle

  23. An automated and reproducible workflow for running and analyzing neural simulations using Lancet and IPython Notebook

    Stevens, J-L., Elver, M. & Bednar, J. A., 2013, In : Frontiers in Neuroinformatics. 7

    Research output: Contribution to journalArticle

  24. An isotropic Gaussian mixture can have more modes than components

    Carreira-Perpinan, M. & Williams, C. K. I., 1 Dec 2003.

    Research output: Working paper

  25. Analysis of Multiplexed Neural Codes Using the Laplacian Pyramid Decomposition

    Molano-Mazon, M., Onken, A., Safaai, H. & Panzeri, S., 15 Sep 2015. 1 p.

    Research output: Contribution to conferenceAbstract

  26. Analysis of Video Feature Learning in Two-Stream CNNs on the Example of Zebrafish Swim Bout Classification

    Breier, B. & Onken, A., 20 Dec 2019.

    Research output: Contribution to conferencePaper

  27. Analysis of a genetic-metabolic oscillator with piecewise linear models

    Chaves, M., Oyarzun, D. & Gouze, J-L., 7 Feb 2019, In : Journal of Theoretical Biology. 462, p. 259-269 11 p.

    Research output: Contribution to journalArticle

  28. Analysis of compound heterozygotes reveals that the mouse floxed Pax6 tm1Ued allele produces abnormal eye phenotypes

    Dorà, N. J., Crookshanks, A. J. F., Leung, K. K. Y., Simpson, T., Mason, J., Price, D. & West, J., 30 May 2016, In : Transgenic Research. p. 1-14 14 p.

    Research output: Contribution to journalArticle

  29. Analysis of individual mouse activity in group housed animals of different inbred strains using a novel automated home cage analysis system.

    Bains, R. S., Cater, H. L., Sillito, R. R., Chartsias, A., Sneddon, D., Concas, D., Keskivali-Bond, P., Lukins, T. C., Wells, S., Acevedo Arozena, A., Nolan, P. M. & Armstrong, J. D., 10 Jun 2016, In : Frontiers in behavioral neuroscience. 10, 106, 22 p.

    Research output: Contribution to journalArticle

  30. Analysis of local and global topographic order in mouse retinocollicular maps

    Willshaw, D. J., Sterratt, D. C. & Teriakidis, A., 29 Jan 2014, In : Journal of Neuroscience. 34, 5, p. 1791-805 15 p.

    Research output: Contribution to journalArticle

  31. Analysis of mouse EphA knockins and knockouts suggests that retinal axons programme target cells to form ordered retinotopic maps

    Willshaw, D., 2006, In : Development. 133, 14, p. 2705-2717 13 p.

    Research output: Contribution to journalArticle

  32. Analysis of proteins in computational models of synaptic plasticity

    Heil, K. F., Wysocka, E., Sorokina, O., Hellgren Kotaleski, J., Simpson, T. I., Armstrong, J. D. & Sterratt, D. C., 28 Jan 2018, bioRxiv, at Cold Spring Harbor Laboratory, 53 p.

    Research output: Working paper

  33. Analysis of simultaneous multielectrode recordings with 4,096 channels: changing dynamics of spontaneous activity in the developing retina

    Hennig, M., Maccione, A., Gandolfo, M., Down, M., Eglen, S., Berdondini, L. & Sernagor, E., 2011, In : BMC Neuroscience. 12, Supplement 1, 2 p., P296.

    Research output: Contribution to journalMeeting abstract

  34. Analysis of the Bacterial Response to Ru(CO) 3 Cl(Glycinate) (CORM-3) and the Inactivated Compound Identifies the Role Played by the Ruthenium Compound and Reveals Sulfur-Containing Species as a Major Target of CORM-3 Action .

    Mclean, S., Begg, R., Jesse, H. E., Mann, B. E., Sanguinetti, G. & Poole, R. K., 10 Dec 2013, In : Antioxidants and Redox Signaling. 19, 17, p. 1999-2012 14 p.

    Research output: Contribution to journalArticle

  35. Analysis of the expression patterns, subcellular localisations and interaction partners of Drosophila proteins using a pigP protein trap library

    Lowe, N., Rees, J. S., Roote, J., Ryder, E., Armean, I. M., Johnson, G., Drummond, E., Spriggs, H., Drummond, J., Magbanua, J. P., Naylor, H., Sanson, B., Bastock, R., Huelsmann, S., Trovisco, V., Landgraf, M., Knowles-Barley, S., Armstrong, J. D., White-Cooper, H., Hansen, C. & 5 others, Phillips, R. G., The UK Drosophila Protein Trap Screening Consortium, Lilley, K. S., Russell, S. & St Johnston, D., 2014, In : Development. 141, 20, p. 3994-4005 12 p.

    Research output: Contribution to journalArticle

  36. Analysis of transcript changes in a heme-deficient mutant of Escherichia coli in response to CORM-3 [Ru(CO)3Cl(glycinate)]

    Wilson, J. L., Mclean, S., Begg, R., Sanguinetti, G. & Poole, R. K., 1 Sep 2015, In : Genomics Data. 5, p. 231-234 4 p.

    Research output: Contribution to journalArticle

  37. Analytic computation of the integrated response in nonlinear reaction-diffusion systems

    López-Caamal, F., García, M. R., Oyarzún, D. A. & Middleton, R. H., 1 Dec 2012, 2012 IEEE 51st IEEE Conference on Decision and Control (CDC). p. 1047-1052 6 p.

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

  38. Analyzing Short-Term Noise Dependencies of Spike-Counts in Macaque Prefrontal Cortex Using Copulas and the Flashlight Transformation

    Onken, A., Grünewälder, S., Munk, M. H. J. & Obermayer, K., 26 Nov 2009, In : PLoS Computational Biology. 5, 11, p. 1-13 13 p., e1000577.

    Research output: Contribution to journalArticle

  39. Anatomically unbiased analysis of renal BOLD magnetic resonance images reveals disruption of corticomedullary gradient during chronic angiotensin II infusion

    Menzies, R., Zammit-Mangion, A., Hollis, L. M., Lennen, R. J., Jansen, M., Webb, D., Mullins, J., Dear, J., Sanguinetti, G. & Bailey, M., Apr 2013, In : The FASEB Journal. 27, p. 910 1 p.

    Research output: Contribution to journalMeeting abstract

  40. Angiogenesis in the human corpus luteum: localization and changes in angiopoietins, tie-2, and vascular endothelial growth factor messenger ribonucleic acid

    Wulff, C., Wilson, H., Largue, P., Duncan, W. C., Armstrong, D. G. & Fraser, H. M., Nov 2000, In : Journal of Clinical Endocrinology & Metabolism. 85, 11, p. 4302-9 8 p.

    Research output: Contribution to journalArticle

  41. Animacy effects on the production of object-dislocated descriptions by Catalan-speaking children

    Prat-Sala, M., Shillcock, R. & Sorace, A., Feb 2000, In : Journal of Child Language. 27, 1, p. 97-117 21 p.

    Research output: Contribution to journalArticle

  42. Anticipation in the Rodent Head Direction System Can Be Explained by an Interaction of Head Movements and Vestibular Firing Properties

    van der Meer, M., Knierim, J. J., Yoganarasimha, D., Wood, E. R. & van Rossum, M. C. W., Oct 2007, In : Journal of Neurophysiology. 98, 4, p. 1883-1897 15 p.

    Research output: Contribution to journalArticle

  43. Approximate Inference in Latent Diffusion Processes from Continuous Time Observations

    Cseke, B., Opper, M. & Sanguinetti, G., 2013, Advances in Neural Information Processing Systems 26 (NIPS 2013). Vol. 26. 9 p.

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

  44. Approximate inference in continuous time Gaussian-Jump processes

    Opper, M., Ruttor, A. & Sanguinetti, G., 2010, Advances in Neural Information Processing Systems 23. Lafferty, J. D., Williams, C. K. I., Shawe-Taylor, J., Zemel, R. S. & Culotta, A. (eds.). p. 1831-1839 9 p.

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

  45. Approximate inference in latent Gaussian-Markov models from continuous time observations

    Cseke, B., Opper, M. & Sanguinetti, G., 2013, Advances in Neural Information Processing Systems 26. Curran Associates Inc, p. 971 979 p.

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

  46. Approximate inference of the bandwidth in multivariate kernel density estimation

    Filippone, M. & Sanguinetti, G., 2011, In : Computational statistics & data analysis. 55, 12, p. 3104 - 3122 19 p.

    Research output: Contribution to journalArticle

  47. Approximation and inference methods for stochastic biochemical kinetics - a tutorial review

    Schnoerr, D., Sanguinetti, G. & Grima, R., 25 Jan 2017, In : Journal of Physics A: Mathematical and Theoretical. 093001.

    Research output: Contribution to journalArticle

  48. Approximation methods for gaussian process regression

    Quiñonero-Candela, J., Rasmussen, C. E. & Williams, C. K. I., Aug 2007, Large-Scale Kernel Machines. Bottou, L., Chapelle, O., DeCoste, D. & Weston, J. (eds.). MIT Press, 24 p.

    Research output: Chapter in Book/Report/Conference proceedingChapter

  49. Arc requires PSD95 for assembly into postsynaptic complexes involved with brain disease and intelligence

    Fernandez, E., Collins, M. O., Frank, R. A. W., Zhu, F., Kopanitsa, M. V., Nithianantharajah, J., Lempriere, S., Fricker, D. G., Elsegood, K. A., McLaughlin, C., Croning, M. D. R., McLean, C., Armstrong, J. D., Hill, W. D., Deary, I., Cencelli, G., Bagni, C., Fromer, M., Purcell, S. M., Pocklington, A. J. & 3 others, Choudhary, J. S., Komiyama, N. & Grant, S., 17 Oct 2017, In : Cell Reports. 21, 3, p. 679-691

    Research output: Contribution to journalArticle

  50. Archetypal Analysis for Nominal Observations

    Seth, S. & Eugster, M., 19 Aug 2015, In : IEEE Transactions on Pattern Analysis and Machine Intelligence. 38, 5, p. 849-861 14 p.

    Research output: Contribution to journalArticle

  51. Are We There Yet? How and When Specific Biotechnologies Will Improve Human Health

    O'Day, E., Hosta‐Rigau, L., Oyarzun, D., Okano, H., de Lorenzo, V., von Kameke, C., Alsafar, H., Cao, C., Chen, G-Q., Ji, W., Roberts, R. J., Ronaghi, M., Yeung, K., Zhang, F. & Lee, S. Y., 10 Jan 2019, In : Biotechnology Journal. 14, 1, p. 1-11 11 p.

    Research output: Contribution to journalArticle

  52. Assessing mouse behaviour throughout the light/dark cycle using automated in-cage analysis tools

    Bains, R. S., Sillito, R. R., Armstrong, J. D., Cater, H. L., Banks, G. & Nolan, P. M., 26 Apr 2017, In : Journal of Neuroscience Methods. 32 p.

    Research output: Contribution to journalArticle

  53. Assessing the validity of a learning analytics expectation instrument: A multinational study

    Whitelock-Wainwright, A., Gasevic, D., Tsai, Y-S., Drachsler, H., Scheffel, M., Muñoz-Merino, P., Tammets, K. & Delgado Kloos, C., 1 Oct 2019, (Accepted/In press) In : Journal of Computer Assisted Learning. 53 p.

    Research output: Contribution to journalArticle

  54. Associating What and Where Using Temporal Cues

    Goddard, N. H., 1993, Proceedings of the 15th Annual Conference of the Cognitive Science Society. Vol. 15.

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

  55. Associative latching dynamics vs. syntax

    Russo, E., Pirmoradian, S. & Treves, A., 2011, Advances in Cognitive Neurodynamics (II): Proceedings of the Second International Conference on Cognitive Neurodynamics - 2009. Springer Netherlands, p. 111-115 5 p.

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

  56. Asymptotically exact inference in differentiable generative models

    Graham, M. & Storkey, A., 22 Apr 2017, Proceedings of the 20th International Conference on Artificial Intelligence and Statistics (AISTATS) 2017. Journal of Machine Learning Research: Workshop and Conference Proceedings, p. 499-508 10 p.

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

  57. Asynchronous inputs and NMDA conductances predict excitatory responses in the cortical-cA1 pathway of the hippocampus

    Longden, K. D. & Willshaw, D. J., 2007, In : Network: Computation in Neural Systems. 18, 4, p. 299-325 27 p.

    Research output: Contribution to journalArticle

  58. Attention as Reward-Driven Optimization of Sensory Processing: Neural Computation

    Chalk, M., Murray, I. & Seriés, P., 18 Jun 2013, In : Neural Computation. 25, 11, p. 2904-2933 30 p.

    Research output: Contribution to journalArticle

  59. Augmenting Image Classifiers Using Data Augmentation Generative Adversarial Networks

    Antoniou, A., Storkey, A. & Edwards, H., 27 Sep 2018, Artificial Neural Networks and Machine Learning – ICANN 2018. Rhodes, Greece, p. 594-603 10 p. (Lecture Notes in Computer Science; vol. 11141).

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

  60. Author Disambiguation: A Nonparametric Topic and Co-authorship Model

    Dai, A. M. & Storkey, A. J., 2009, Proceedings of NIPS Workshop on Applications for Topic Models Text and Beyond. 4 p.

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

  61. Autistic traits, but not schizotypy, predict increased weighting of sensory information in Bayesian visual integration

    Karvelis, P., Seitz, A. R., Lawrie, S. & Series, P., 14 May 2018, In : eLIFE. 44 p.

    Research output: Contribution to journalArticle

  62. Autoencoding Variational Inference for Topic Models

    Srivastava, A. & Sutton, C., 26 Apr 2017, Proceedings for the 5th International Conference on Learning Representations. 12 p.

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

  63. Autofolding for Source Code Summarization

    Fowkes, J., Chanthirasegaran, P., Ranca, R., Allamanis, M., Lapata, M. & Sutton, C., 6 Feb 2017, In : IEEE Transactions on Software Engineering. 1 p.

    Research output: Contribution to journalArticle

  64. Automated assessment of tract similarity in group diffusion MRI data

    Clayden, J. D., Bastin, M. & Storkey, A., 2006, Proceedings of the ISMRM, 14th Scientific Meeting Exhibition, Seattle.

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

  65. Automated extraction of meaningful pathways from quantitative proteomics data

    Noirel, J., Ow, S. Y., Sanguinetti, G., Jaramillo, A. & Wright, P. C., Mar 2008, In : Briefings in functional genomics & proteomics. 7, 2, p. 136-146 11 p.

    Research output: Contribution to journalArticle

  66. Automated recording of home cage activity and temperature of individual rats housed in social groups: The Rodent Big Brother project

    Redfern, W. S., Tse, K., Grant, C., Keerie, A., Simpson, D. J., Pedersen, J. C., Rimmer, V., Leslie, L., Klein, S. K., Karp, N. A., Sillito, R., Chartsias, A., Lukins, T., Heward, J., Vickers, C., Chapman, K., Armstrong, J. D. & Homberg, J. (ed.), 6 Sep 2017, In : PLoS ONE. 12, 9, p. 1-26 26 p., e0181068.

    Research output: Contribution to journalArticle

  67. Automatic Determination of the Number of Clusters Using Spectral Algorithms

    Sanguinetti, G., Laidler, J. & Lawrence, N. D., 1 Sep 2005, Machine Learning for Signal Processing, 2005 IEEE Workshop on. Institute of Electrical and Electronics Engineers (IEEE), p. 55-60 6 p.

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

  68. Automatic Exploration of Datacenter Performance Regimes

    Bodik, P., Griffith, R., Sutton, C., Fox, A., Jordan, M. I. & Patterson, D. A., 2009, Proceedings of the 1st Workshop on Automated Control for Datacenters and Clouds (ACDC 2009). New York, NY, USA: ACM, p. 1-6 6 p.

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

  69. Automatic classification of arrhythmic beats using Gaussian Processes

    Skolidis, G., Clayton, R. H. & Sanguinetti, G., Sep 2008, Computers in Cardiology, 2008. Institute of Electrical and Electronics Engineers (IEEE), p. 921-924 4 p.

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

  70. Automatically Extracting Drosophila Courtship Behaviour Statistics from Video

    Heward, J. A., Lukins, T. C., Dewar, M. A. & Armstrong, D., 2008, Workshop on the Visual Observation and Analysis of Animal and Insect Behavior (held at ICPR2008). 4 p.

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

  71. Automatically determining active investigation in rodents using contour analysis

    Lukins, T. C., Dewar, M., Crook, P. A., Heward, J. A. & Armstrong, J. D., 2008, Proceedings of Measuring Behavior 2008. p. 267-268

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

  72. Automating the Calibration of a Neonatal Condition Monitoring System

    Williams, C. K. I. & Stanculescu, I., 2011, Artificial Intelligence in Medicine: 13th Conference on Artificial Intelligence in Medicine, AIME 2011, Bled, Slovenia, July 2-6, 2011. Proceedings. Peleg, M., Lavrac, N. & Combi, C. (eds.). Springer-Verlag GmbH, p. 240-249 10 p. (Lecture Notes in Computer Science; vol. 6747).

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

  73. Autoregressive Hidden Markov Models for the Early Detection of Neonatal Sepsis

    Stanculescu, I., Williams, C. K. I. & Freer, Y., 1 Sep 2014, In : IEEE Journal of Biomedical and Health Informatics. 18, 5, p. 1560-1570 11 p.

    Research output: Contribution to journalArticle

  74. Autoregressive Point-Processes as Latent State-Space Models: a Moment-Closure Approach to Fluctuations and Autocorrelations

    Rule, M. & Sanguinetti, G., 27 Aug 2018, In : Neural Computation. 34 p.

    Research output: Contribution to journalArticle

  75. Aye or naw, whit dae ye hink? Scottish independence and linguistic identity on social media

    Shoemark, P., Sur, D., Shrimpton, L., Murray, I. & Goldwater, S., 7 Apr 2017, European Chapter of the Association for Computational Linguistics (EACL 2017). Valencia, Spain : Association for Computational Linguistics, p. 1239–1248 10 p.

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

  76. BERT and PALs: Projected Attention Layers for Efficient Adaptation in Multi-Task Learning

    Cooper Stickland, A. & Murray, I., 3 Jul 2019, Proceedings of the 36th International Conference on Machine Learning (ICML). Chaudhuri, K. & Salakhutdinov, R. (eds.). Long Beach, USA: PMLR, Vol. 97. p. 5986-5995 12 p. (PMLR; vol. 97).

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

  77. BLISS: an artificial language for learnability studies

    Pirmoradian, S. & Treves, A., 20 Oct 2011, In : Cognitive Computation. 3, 4, p. 539-553 15 p.

    Research output: Contribution to journalArticle

  78. BONSEYES: Platform for Open Development of Systems of Artificial Intelligence: Invited Paper

    Llewellynn, T., Fernández-Carrobles, M. M., Deniz, O., Fricker, S., Storkey, A., Pazos, N., Velikic, G., Leufgen, K., Dahyot, R., Koller, S., Goumas, G., Leitner, P., Dasika, G., Wang, L. & Tutschku, K., 15 May 2017, Proceedings of the Computing Frontiers Conference. New York, NY, USA: ACM, p. 299-304 6 p. (CF'17).

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

  79. BPRMeth: a flexible Bioconductor package for modelling methylation profiles

    Kapourani, C-A. & Sanguinetti, G., 15 Jul 2018, In : Bioinformatics. 34, 14, p. 2485-2486 2 p.

    Research output: Contribution to journalArticle

  80. BRIE: transcriptome-wide splicing quantication in single cells

    Huang, Y. & Sanguinetti, G., 27 Jun 2017, In : Genome Biology. 18, 123, p. 1-11 11 p.

    Research output: Contribution to journalArticle

  81. Ballooning Delta-prime in the Second Stable Region

    Bishop, C. M., Hastie, R. J., Sykes, A. & Wilson, H. R., 1 Jan 1990, In : Physics of Fluids B. 2, p. 3052-3053 2 p.

    Research output: Contribution to journalArticle

  82. Ballooning stability analysis of JET H-mode discharges

    O'Brien, D. P., Galvao, R., Keilhacker, M., Lazzaro, E., Watkins, M. L. & Bishop, C. M., 1989, Proceedings 16th European Conference on Controlled Fusion and Plasma Physics. Vol. 1. p. 229-232 4 p.

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

  83. Band tails in a disordered system

    van Rossum, M., Nieuwenhuizen, T. M., Hofstetter, E. & Schreiber, M., 1993, Photonic band gaps and localization: Proceedings of a NATO ARW on Localization and Propagation of Classical Waves in Random and Periodic Structures held in Aghia Pelaghia, Heraklion, Crete, May 26-30, 1992 . Soukoulis, C. M. (ed.). New York: Springer US, p. 509-513 5 p. (Nato Science Series B:; vol. 308).

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

  84. Basic Integrated Modelling: A Case Study

    Salgado, M. E. & Oyarzún, D. R., 1 Jul 2006, In : International Journal of Electrical Engineering Education. 43, 3, p. 217-231 15 p.

    Research output: Contribution to journalArticle

  85. Bat detective - Deep learning tools for bat acoustic signal detection

    Mac Aodha, O., Gibb, R., Barlow, K. E., Browning, E., Firman, M., Freeman, R., Harder, B., Kinsey, L., Mead, G. R., Newson, S. E., Pandourski, I., Parsons, S., Russ, J., Szodoray-Paradi, A., Szodoray-Paradi, F., Tilova, E., Girolami, M., Brostow, G. & Jones, K. E., 8 Mar 2018, In : PLoS Computational Biology. 14, 3, p. 1-19 19 p.

    Research output: Contribution to journalArticle

  86. Bayesian Adversarial Spheres: Bayesian Inference and Adversarial Examples in a Noiseless Setting

    Bekasovs, A. & Murray, I., 16 Nov 2018, (Accepted/In press) p. 1-6. 6 p.

    Research output: Contribution to conferencePaper

  87. Bayesian Classification with Gaussian Processes

    Williams, C. K. I. & Barber, D., Dec 1998, In : IEEE Transactions on Pattern Analysis and Machine Intelligence. 20, 12, p. 1342-1351 10 p.

    Research output: Contribution to journalArticle

  88. Bayesian Inference of Atomistic Structure in Functional Materials

    Todorovic, M., Gutmann, M., Corander, J. & Rinke, P., 18 Mar 2019, In : npj Computational Materials. 5, 7 p., 35.

    Research output: Contribution to journalArticle

  89. Bayesian Learning in Undirected Graphical Models: Approximate MCMC algorithms

    Murray, I. & Ghahramani, Z., 2004, Proceedings of the 20th Annual Conference on Uncertainty in Artificial Intelligence (UAI-04). Arlington, Virginia: AUAI Press, p. 392-399 8 p.

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

  90. Bayesian Machine Learning Approaches for Longitudinal Latent Class Modelling to Define Wheezing Phenotypes to Elucidate Environmental Associates

    Custovic, A., Simpson, A., Belgrave, D., Buchan, I. & Bishop, C., 2012, In : Quaderni di statistica. 14, 14, 4 p.

    Research output: Contribution to journalArticle

  91. Bayesian Modeling of Dependency Trees Using Hierarchical Pitman-Yor Priors

    Wallach, H., Sutton, C. & McCallum, A., 2008, ICML Workshop on Prior Knowledge for Text and Language. p. 15-20 6 p.

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

  92. Bayesian Multitask Classification With Gaussian Process Priors

    Skolidis, G. & Sanguinetti, G., 1 Dec 2011, In : IEEE Transactions on Neural Networks. 22, 12, p. 2011-2021 11 p.

    Research output: Contribution to journalArticle

  93. Bayesian Neural Networks

    Bishop, C. M., Jul 1997, In : The Journal of the Brazilian Computer Society. 4, 1, p. 61–68 8 p.

    Research output: Contribution to journalArticle

  94. Bayesian Optimization for Likelihood-Free Inference of Simulator-Based Statistical Models

    Gutmann, M. U. & Corander, J., 2016, In : Journal of Machine Learning Research. 17, 125, p. 1-47 47 p.

    Research output: Contribution to journalArticle

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