Edinburgh Research Explorer

Institute for Adaptive and Neural Computation

Organisational unit: Research Institute

  1. Probabilistic computation underlying sequence learning in a spiking attractor memory network

    Tully, P., Lindén, H., Hennig, M. H. & Lansner, A., 1 Jan 2013, In : BMC Neuroscience. 14, 2 p.

    Research output: Contribution to journalArticle

  2. Spike-Based Bayesian-Hebbian Learning of Temporal Sequences

    Tully, P. J., Lindén, H., Hennig, M. H. & Lansner, A., 23 May 2016, In : PLoS Computational Biology. 12, 5, 35 p., e1004954.

    Research output: Contribution to journalArticle

  3. Synaptic and nonsynaptic plasticity approximating probabilistic inference

    Tully, P. J., Hennig, M. H. & Lansner, A., 2014, In : Frontiers in synaptic neuroscience. 6, 8.

    Research output: Contribution to journalArticle

  4. BlockSwap: Fisher-guided Block Substitution for Network Compression on a Budget

    Turner, J., Crowley, E., O'Boyle, M., Storkey, A. & Gray, G., 1 Jan 2020, (Accepted/In press) Proceedings to the International Conference on Learning Representations 2020. 15 p.

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

  5. Characterising Across-Stack Optimisations for Deep Convolutional Neural Networks

    Turner, J., Cano Reyes, J., Radu, V., Crowley, E., O'Boyle, M. & Storkey, A., 13 Dec 2018, Proceedings of the - Workload Characterization (IISWC), 2018 IEEE International Symposium on. Raleigh, North Carolina, USA: Institute of Electrical and Electronics Engineers (IEEE), p. 101-110 10 p.

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

  6. Functional conservation of Pax6 regulatory elements in humans and mice demonstrated with a novel transgenic reporter mouse

    Tyas, D. A., Simpson, T. I., Carr, C. B., Kleinjan, D. A., van Heyningen, V., Mason, J. O. & Price, D., 2006, In : BMC Developmental Biology. 6, 11 p., 21.

    Research output: Contribution to journalArticle

  7. 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

  8. 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

  9. 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)

  10. RNADE: The real-valued neural autoregressive density-estimator

    Uria, B., Murray, I. & Larochelle, H., 2013, Advances in Neural Information Processing Systems 26. p. 2175-2183 9 p.

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