Edinburgh Research Explorer

Institute for Adaptive and Neural Computation

Organisational unit: Research Institute

  1. Gaussian process modeling in approximate Bayesian computation to estimate horizontal gene transfer in bacteria

    Järvenpää, M., Gutmann, M., Vehtari, A. & Marttinen, P., 13 Nov 2018, In : Annals of Applied Statistics. 12, 4, p. 2228-2251 24 p.

    Research output: Contribution to journalArticle

  2. Gaussian processes for machine learning

    Rasmussen, C. E. & Williams, C. K. I., 2006, MIT Press. 272 p.

    Research output: Book/ReportBook

  3. Gaussian processes for switching regimes

    Storkey, A., 1998, ICANN 98: Proceedings of the 8th International Conference on Artificial Neural Networks, Skövde, Sweden, 2–4 September 1998. Springer London, p. 621-626 6 p. (Perspectives in Neural Computing).

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

  4. Gene Network Reconstruction Using a Distributed Genetic Algorithm with a Backprop Local Search

    Cumiskey, M., Levine, J. & Armstrong, D., 2003, Applications of Evolutionary Computing: EvoWorkshops 2003: EvoBIO, EvoCOP, EvoIASP, EvoMUSART, EvoROB, and EvoSTIM Essex, UK, April 14–16, 2003 Proceedings. Cagnoni, S., Johnson, C., Cardalda, J., Marchiori, E., Corne, D., Meyer, J-A., Gottlieb, J., Middendorf, M., Guillot, A., Raidl, G. & Hart, E. (eds.). Springer Berlin Heidelberg, p. 177-181 5 p. (Lecture Notes in Computer Science; vol. 2611).

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

  5. Gene Regulatory Network Inference: An Introductory Survey

    Huynh-Thu, V. A. & Sanguinetti, G., 2019, Gene Regulatory Networks: Methods and Protocols. Sanguinetti, G. & Huynh-Thu, V. A. (eds.). New York, NY: Springer New York LLC, p. 1-23 23 p.

    Research output: Chapter in Book/Report/Conference proceedingChapter

  6. Gene Regulatory Networks: Methods and Protocols

    Sanguinetti, G. (ed.) & Huynh-Thu, V. A. (ed.), 2019, Humana Press. 285 p. (Methods in Molecular Biology Series Volume; vol. 1883)

    Research output: Book/ReportBook

  7. Gene switching rate determines response to extrinsic perturbations in the self-activation transcriptional network motif

    De Franciscis, S., Caravagna, G., Mauri, G. & D’onofrio, A., 2016, In : Scientific Reports. 6, 15 p., 26980.

    Research output: Contribution to journalArticle

  8. Generalised propagation for fast Fourier transforms with partial or missing data

    Storkey, AJ., 2004, ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 16: Proceedings of the 2003 Conference. Thrun, S., Saul, K. & Scholkopf, B. (eds.). CAMBRIDGE: MIT Press, p. 433-440 8 p. (ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS; vol. 16).

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

  9. Generalizability of EMG decoding using local field potentials

    Krasoulis, A., Hall, T. M., Vijayakumar, S., Jackson, A. & Nazarpour, K., 1 Aug 2014, Engineering in Medicine and Biology Society (EMBC), 2014 36th Annual International Conference of the IEEE. Institute of Electrical and Electronics Engineers (IEEE), p. 1630-1633 4 p.

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

  10. Generating confidence intervals on biological networks

    Thorne, T. & Stumpf, M. P. H., 30 Nov 2007, In : BMC Bioinformatics. 8, 467.

    Research output: Contribution to journalArticle

  11. Generation of a 'Pax6 GFP reporter' transgenic mouse

    Tyas, D. A., Kleinjan, D. A., Simpson, T. I., van Heyningen, V., Mason, J. O. & Price, D. J., Nov 2002, In : Molecular Biology of the Cell. 13, Supplement, p. 519A-519A 1 p.

    Research output: Contribution to journalMeeting abstract

  12. Generation of time delays: simplified models of intracellular signalling in cerebellar Purkinje cells

    Steuber, V., Willshaw, D. & Van Ooyen, A., 2006, In : Network: Computation in Neural Systems. 17, 2, p. 173-91 19 p.

    Research output: Contribution to journalArticle

  13. Generative Ratio Matching Networks

    Srivastava, A., Xu, K., Gutmann, M. & Sutton, C., 30 Apr 2020, Proceedings of the International Conference on Learning Representations 2020. p. 1-18 18 p.

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

  14. Genetic analysis of the Drosophila ellipsoid body neuropil: Organization and development of the central complex

    Renn, S. C. P., Armstrong, J. D., Yang, M., Wang, Z., An, X., Kaiser, K. & Taghert, P. H., 1999, In : Journal of neurobiology. 41, 2, p. 189-207 19 p.

    Research output: Contribution to journalArticle

  15. Genetics of Graviperception in Animals

    Beckingham, K. M., Texada, M. J., Baker, D. A., Munjaal, R. & Armstrong, J. D., 2005, In : Advances in genetics. 55, p. 105-145 41 p.

    Research output: Contribution to journalArticle

  16. Genome-wide CRISPR screen Identifies Host Dependency Factors for Influenza A Virus Infection

    Li, B., Clohisey, S. M., Chia, B. S., Wang, B., Cui, A., Eisenhaure, T., Schweitzer, L. D., Hoover, P., Parkinson, N. J., Nachshon, A., Smith, N., Regan, T., Farr, D., Gutmann, M. U., Bukhari, S. I., Law, A., Sangesland, M., Gat-viks, I., Digard, P., Vasudevan, S. & 5 others, Lingwood, D., Dockrell, D. H., Doench, J. G., Baillie, J. K. & Hacohen, N., 9 Jan 2020, In : Nature Communications. 11, 1

    Research output: Contribution to journalArticle

  17. Geocoding of trees from street addresses and street-level images

    Laumer, D., Lang, N., van Doorn, N., Mac Aodha, O., Perona, P. & Dirk Wegner, J., 30 Apr 2020, In : ISPRS Journal of Photogrammetry and Remote Sensing. 162, p. 125-136 12 p.

    Research output: Contribution to journalArticle

  18. Geometric fluid approximation for general continuous-time Markov chains

    Michaelides, M., Hillston, J. & Sanguinetti, G., Sep 2019, In : Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences. 475, 2229, 25 p.

    Research output: Contribution to journalArticle

  19. Geppetto: a reusable modular open platform for exploring neuroscience data and models

    Cantarelli, M., Marin, B., Quintana, A., Earnshaw, M., Court, R., Gleeson, P., Dura-bernal, S., Silver, R. A. & Idili, G., 19 Oct 2018, In : Philosophical Transactions of the Royal Society B: Biological Sciences. 373, 1758, p. 1-13 13 p.

    Research output: Contribution to journalArticle

  20. Gesturing at Architecture: Experiences & Issues with New Forms of Interaction

    Morgan, E., Gunes, H. & Harris, D., 2013, Proceedings Experiencing Interactivity in Public Spaces: Workshop at CHI'13. p. 117-121 5 p.

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

  21. Global Gene Regulation in Metabolic Networks

    Oyarzún, D. A. & Chaves, M., Jan 2011, In : IFAC Proceedings Volumes (IFAC-PapersOnline). 44, 1, p. 14838 - 14843

    Research output: Contribution to journalArticle

  22. Goals and resource constraints in CARMA

    Hillston, J., Georgoulas, A. & Piho, P., 9 May 2018, In : Electronic Notes in Theoretical Computer Science. 337, p. 155-172 18 p.

    Research output: Contribution to journalArticle

  23. Goldman-Hodgkin-Katz Equations

    Sterratt, D. C., 2015, Encyclopedia of Computational Neuroscience. Jaeger, D. & Jung, R. (eds.). Springer New York, p. 1300-1302 3 p.

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

  24. Graphical modelling of molecular networks underlying sporadic inclusion body myositis

    Thorne, T., Fratta, P., Hanna, M. G., Cortese, A., Plagnol, V., Fisher, E. M. & Stumpf, M. P. H., 1 Jul 2013, In : Molecular BioSystems. 9, 7, p. 1736-1742 7 p.

    Research output: Contribution to journalArticle

  25. Gravitaxis in Drosophila melanogaster: a forward genetic screen

    Armstrong, J. D., Texada, M. J., Munjaal, R., Baker, D. A. & Beckingham, K. M., 2006, In : Genes, Brain and Behavior. 5, 3, p. 222-239 18 p.

    Research output: Contribution to journalArticle

  26. Greater intermanual transfer in the elderly suggests age-related bilateral motor cortex activation is compensatory

    Graziadio, S., Nazarpour, K., Gretenkord, S., Jackson, A. & Eyre, J. A., 9 Jan 2015, In : Journal of Motor Behavior. 47, 1, p. 47-55

    Research output: Contribution to journalArticle

  27. Greedy Learning of Binary Latent Trees

    Harmeling, S. & Williams, C. K. I., Jun 2011, In : IEEE Transactions on Pattern Analysis and Machine Intelligence. 33, 6, p. 1087-1097 11 p.

    Research output: Contribution to journalArticle

  28. Greedy learning of multiple objects in images using robust statistics and factorial learning

    Williams, C. K. I. & Titsias, M. K., 2004, In : Neural Computation. 16, 5, p. 1039-1062 24 p.

    Research output: Contribution to journalArticle

  29. Growth defects and loss-of-function in synthetic gene circuits

    Nikolados, E-M., Weisse, A., Ceroni, F. & Oyarzún, D., 1 Jun 2019, In : ACS Synthetic Biology. 8, 6, p. 1231−1240 10 p.

    Research output: Contribution to journalArticle

  30. Guest Editorial

    Nazarpour, K., Cipriani, C., Farina, D. & Kuiken, T., 8 Jul 2014, In : IEEE Transactions on Neural Systems and Rehabilitation Engineering. 22, 4, p. 711-715 5 p.

    Research output: Contribution to journalEditorial

  31. Guided Incremental Construction of Belief Networks

    Sutton, C. A., Burns, B., Morrison, C. & Cohen, P. R., 2003, Advances in Intelligent Data Analysis V: 5th International Symposium on Intelligent Data Analysis, IDA 2003, Berlin, Germany, August 28-30, 2003. Proceedings. R. Berthold, M., Lenz, H-J., Bradley, E., Kruse, R. & Borgelt, C. (eds.). Springer-Verlag GmbH, p. 533-543 11 p. (Lecture Notes in Computer Science; vol. 2810).

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

  32. H2 optimal ripple-free deadbeat controller design

    Salgado, M. E., Oyarzún, D. A. & Silva, E. I., 2007, In : Automatica. 43, 11, p. 1961 - 1967 7 p.

    Research output: Contribution to journalArticle

  33. HOUDINI: Lifelong Learning as Program Synthesis

    Valkov, L., Chaudhari, D., Srivastava, A., Sutton, C. & Chaudhuri, S., 2018, Thirty-second Conference on Neural Information Processing Systems (NIPS 2018). Montreal, Canada, p. 1-12 12 p.

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

  34. Hallucinations in Charles Bonnet Syndrome Induced by Homeostasis: a Deep Boltzmann Machine Model

    Reichert, D. P., Series, P. & Storkey, A., 2010, Advances in Neural Information Processing Systems 23. Vol. 23. p. 2020-2028 9 p.

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

  35. Handbook of Neural Computation

    Bishop, C. M., 1996, Handbook of Neural Computation. Oxford University Press

    Research output: Chapter in Book/Report/Conference proceedingChapter

  36. Harmonising chorales by probabilistic inference

    Allan, M. & Williams, C. K. I., 2005, Advances in Neural Information Processing Systems 17 (NIPS 2004). MIT Press, p. 25-32 8 p.

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

  37. Heart Cells are aMAZEing

    Kudryashova, N. & Panfilov, A., 17 Apr 2020, The Art of Theoretical Biology. Matthäus, F., Matthäus, S., Harris, S. & Hillen, T. (eds.). Cham: Springer International Publishing, p. 138-139 2 p.

    Research output: Chapter in Book/Report/Conference proceedingChapter

  38. Heat-Pulse Propagation in Tokamaks and the Role of Density Perturbations

    Bishop, C. M. & Connor, J. W., 1 Jan 1990, In : Plasma physics and controlled fusion. 32, 3, p. 203-211 9 p.

    Research output: Contribution to journalArticle

  39. Hebbian Learning of the Statistical and Geometrical Structure of Visual Input

    Bednar, J. A., 2014, Neuromathematics of Vision: Lecture Notes in Morphogenesis. Springer Berlin Heidelberg, p. 335-366 Chapter 8. (Neuromathematics of Vision).

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

  40. Hemispheric dissociation and dyslexia in a computational model of reading

    Monaghan, P. & Shillcock, R., Dec 2008, In : Brain and Language. 107, 3, p. 185-193 9 p.

    Research output: Contribution to journalArticle

  41. Hierarchical Subquery Evaluation for Active Learning on a Graph

    Mac Aodha, O., Campbell, N. D. F., Kautz, J. & Brostow, G. J., 25 Sep 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition. Institute of Electrical and Electronics Engineers (IEEE), p. 564-571 8 p.

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

  42. High resolution spatiotemporal analysis of mouse retinal waves during postnatal development

    Sernagor, E., Hennig, M., Maccione, A., Gandolfo, M., Down, M., van Coppenhagen, J., Eglen, S. & Berdondini, L., 2011, Proc. Society for Neuroscience Annual Meeting (SFN'11).

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

  43. Higher order methylation features for clustering and prediction in epigenomic studies

    Kapourani, A. & Sanguinetti, G., 1 Sep 2016, In : Bioinformatics. 33, 8, p. i405-i412 12 p.

    Research output: Contribution to journalArticle

  44. Higher rates of anxiety found in self-reported grapheme-colour synaesthetes

    Carmichael, D. A., Shillcock, R. & Simner, J., 2014.

    Research output: Contribution to conferencePoster

  45. Homeostasis in large networks of neurons through the Ising model - do higher order interactions matter?

    Panas, D., Maccione, A., Berdondini, L. & Hennig, M. H., 1 Jan 2013, In : BMC Neuroscience. 14, Suppl 1, p. P166

    Research output: Contribution to journalArticle

  46. Homeostasis of intrinsic excitability in hippocampal neurones: dynamics and mechanism of the response to chronic depolarization

    O'Leary, T., van Rossum, M. C. W. & Wyllie, D. J. A., Jan 2010, In : Journal of Physiology. 588, 1, p. 157-170 14 p.

    Research output: Contribution to journalArticle

  47. Homeostatic Plasticity in a Model of V1 Orientation Map Development.

    Law, J. S. & Bednar, J. A., 2007.

    Research output: Contribution to conferencePoster

  48. Homeostatic intrinsic plasticity, neural heterogeneity and memory maintenance

    Sweeney, Y., Hellgren-Kotaleski, J. & Hennig, M., Dec 2015, In : BMC Neuroscience. 16, 1, p. 1-2 2 p.

    Research output: Contribution to journalArticle

  49. Hopfield learning rule with high capacity storage of time-correlated patterns

    Storkey, A. & Valabregue, R., 9 Oct 1997, In : Electronics Letters. 33, 21, p. 1803-1804 2 p.

    Research output: Contribution to journalArticle

  50. Host-circuit interactions explain unexpected behavior of a gene circuit

    Boada, Y., Vignoni, A., Oyarzún, D. & Picó, J., 2018, In : IFAC-PapersOnLine. 51, 19, p. 86 - 89 4 p.

    Research output: Contribution to journalArticle

  51. How arbitrary is language?

    Monaghan, P., Shillcock, R. C., Christiansen, M. H. & Kirby, S., 19 Sep 2014, In : Philosophical Transactions of the Royal Society B: Biological Sciences. 369, 1651, 12 p., 20130299.

    Research output: Contribution to journalArticle

  52. How biased are maximum entropy models?

    Macke, J. H., Murray, I. & Latham, P. E., 2011, Advances in Neural Information Processing Systems 24. Shawe-Taylor, J., Zemel, R. S., Bartlett, P., Pereira, F. C. N. & Weinberger, K. Q. (eds.). p. 2034-2042 9 p.

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

  53. How do meters mediate? Energy meters, boundary objects and household transitions in Australia and the United Kingdom

    Lovell, H., Pullinger, M. & Webb, J., 7 Sep 2017, In : Energy Research & Social Science. 34, p. 252-259 7 p.

    Research output: Contribution to journalArticle

  54. How do we start? An Approach to Learning Analytics Adoption in Higher Education

    Gasevic, D., Tsai, Y-S., Dawson, S. & Pardo, A., 12 Jun 2019, In : International Journal of Information and Learning Technology. 12 p.

    Research output: Contribution to journalArticle

  55. How plastic is the "slow speeds prior"?

    Sotiropoulos, G., Seitz, A. & Series, P., 2012.

    Research output: Contribution to conferencePoster

  56. How relative stability between visual cues affects cue control of CA1 place cells

    Huang, Y-C. S., Dudchenko, P. A., van Rossum, M. C. W. & Wood, E., 2008.

    Research output: Contribution to conferencePoster

  57. How to pretend that correlated variables are independent by using difference observations

    Williams, C. K. I., Jan 2005, In : Neural Computation. 17, 1, p. 1-6 6 p.

    Research output: Contribution to journalArticle

  58. How to train your MAML

    Antoniou, A., Edwards, H. & Storkey, A., 2019. 11 p.

    Research output: Contribution to conferencePaper

  59. HuD is a neural translation enhancer acting on mTORC1-responsive genes and counteracted by the Y3 small non-coding RNA

    Tebaldi, T., Zuccotti, P., Peroni, D., Köhn, M., Gasperini, L., Potrich, V., Bonazza, V., Dudnakova, T., Rossi, A., Sanguinetti, G., Conti, L., Macchi, P., D'Agostino, V., Viero, G., Tollervey, D., Hüttelmaier, S. & Quattrone, A., 19 Jul 2018, In : Molecular Cell. 71, 2, p. 256-270 26 p.

    Research output: Contribution to journalArticle

  60. 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

  61. 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

  62. 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

  63. Identification of sensory information in mixed nerves using multi-channel cuff electrodes for closed loop neural prostheses

    Brunton, E., Blau, C., Silveira, C. & Nazarpour, K., 15 Aug 2017, 2017 8th International IEEE/EMBS Conference on Neural Engineering (NER). Institute of Electrical and Electronics Engineers (IEEE), p. 391-394 4 p.

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

  64. 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

  65. 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

  66. 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

  67. Identifying needs for learning analytics adoption in Latin American universities: A mixed-methods approach

    Hilliger, I., Ortiz-Rojas, M., Pesántez-Cabrera, P., Scheihing, E., Tsai, Y-S., Muñoz-Merino, P. J., Broos, T., Whitelock-Wainwright, A. & Pérez-Sanagustín, M., 30 Apr 2020, In : Internet and Higher Education. 45, 9 p., 100726.

    Research output: Contribution to journalArticle

  68. 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

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

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

    Research output: Contribution to conferencePoster

  70. 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

  71. 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

  72. 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

  73. 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

  74. 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

  75. 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

  76. 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

  77. Improved prosthetic hand control with concurrent use of myoelectric and inertial measurements

    Krasoulis, A., Kyranou, I., Erden, M. S., Nazarpour, K. & Vijayakumar, S., 11 Jul 2017, In : Journal of Neuroengineering and Rehabilitation. 14, 1, p. 1-14 14 p., 71.

    Research output: Contribution to journalArticle

  78. 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

  79. Improvement in modelling of physiological tremor by inclusion of grip force in quaternion weighted Fourier linear combiner

    Adhikari, K., Tatinati, S., Veluvolu, K. C. & Nazarpour, K., 2 Dec 2015, 2nd IET International Conference on Intelligent Signal Processing 2015 (ISP). IET, p. 1-5 5 p.

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

  80. 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

  81. 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

  82. Incoherent dictionary pair learning: application to a novel open-source database of Chinese numbers

    Abolghasemi, V., Chen, M., Alameer, A., Ferdowsi, S., Chambers, J. & Nazarpour, K., 1 Apr 2018, In : IEEE Signal Processing Letters. 25, 4, p. 472 - 476 5 p.

    Research output: Contribution to journalArticle

  83. 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

  84. 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

  85. 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

  86. 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

  87. 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

  88. 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

  89. Influence of nerve cuff channel count and implantation site on the separability of afferent ENG

    Silveira, C., Brunton, E., Spendiff, S. & Nazarpour, K., 1 Aug 2018, In : Journal of Neural Engineering. 15, 4, p. 1-12 12 p., 046004 .

    Research output: Contribution to journalArticle

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