Edinburgh Research Explorer

Institute for Adaptive and Neural Computation

Organisational unit: Research Institute

  1. 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

  2. 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)

  3. 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

  4. 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

  5. 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

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

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

    Research output: Contribution to conferencePaper

  7. 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

  8. 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