Edinburgh Research Explorer

Institute for Adaptive and Neural Computation

Organisational unit: Research Institute

  1. A Bayesian Approach to Parameter Inference in Queueing Networks

    Wang, W., Casale, G. & Sutton, C., Aug 2016, In : ACM Transactions on Modeling and Computer Simulation. 27, 1, 26 p., 2.

    Research output: Contribution to journalArticle

  2. A Bayesian Network Model for Interesting Itemsets

    Fowkes, J. & Sutton, C., 4 Sep 2016, The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery (ECML-PKDD 2016). Riva del Garda, Italy: Springer, Cham, p. 410-425 16 p. (Lecture Notes in Computer Science ; vol. 9852).

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

  3. A Bayesian approach for structure learning in oscillating regulatory networks

    Trejo-Banos, D., Millar, A. & Sanguinetti, G., 14 Jul 2015, In : Bioinformatics. 31, 22, p. 3617-3624 8 p.

    Research output: Contribution to journalArticle

  4. A Biophysical model of long-term potentiation and synaptic tagging

    Barrett, A., Billings, G., Morris, R. G. M. & van Rossum, M. C. W., 2007.

    Research output: Contribution to conferencePoster

  5. A CONNECTIONIST MODEL OF PRELEXICAL PROCESSING IN SPOKEN WORD RECOGNITION

    LEVY, J., CHATER, N. & Shillcock, R., 1992, In : International Journal of Psychology. 27, 3-4, p. 63-63 1 p.

    Research output: Contribution to journalArticle

  6. A Case Study on Meta-generalising: A Gaussian Processes Approach

    Skolidis, G. & Sanguinetti, G., 1 Mar 2012, In : Journal of Machine Learning Research. 13, 1, p. 691-721 31 p.

    Research output: Contribution to journalArticle

  7. A Comparison of Frequentist and Bayesian Approaches to Latent Class Modelling of Susceptibility to Asthma and Patterns of Antibiotic Prescriptions in Early Life

    Belgrave, D., Bishop, C., Custovic, A., Simpson, A., Semic-Jusufagic, A., Pickles, A. & Buchan, I., 2011, Proceedings of the 26th International Workshop on Statistical Modelling. Valencia (Spain). p. 75-78 4 p.

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

  8. A Composable Strategy for Shredded Document Reconstruction

    Ranca, R. & Murray, I., 2013, Computer Analysis of Images and Patterns. Wilson, R., Hancock, E., Bors, A. & Smith, W. (eds.). Springer-Verlag GmbH, p. 324-331 8 p. (Lecture Notes in Computer Science; vol. 8048).

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

  9. A Convolutional Attention Network for Extreme Summarization of Source Code

    Allamanis, M., Peng, H. & Sutton, C., 24 Jun 2016, Proceedings of The 33rd International Conference on Machine Learning, PMLR. New York, United States: PMLR, Vol. 48. p. 2091-2100 10 p.

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

  10. A Deep and Tractable Density Estimator

    Uria, B., Murray, I. & Larochelle, H., 2014, Proceedings of The 31st International Conference on Machine Learning. Beijing, China: Journal of Machine Learning Research: Workshop and Conference Proceedings, Vol. 32. p. 467-475 9 p. (Journal of Machine Learning Research: Workshop and Conference Proceedings; vol. 32).

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

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