Edinburgh Research Explorer

Institute for Adaptive and Neural Computation

Organisational unit: Research Institute

  1. Probabilistic Principal Component Analysis

    Tipping, M. E. & Bishop, C. M., 1999, In : Journal of the Royal Statistical Society: Series B. 61, 3, p. 611-622 12 p.

    Research output: Contribution to journalArticle

  2. Sequential Learning of Layered Models from Video

    Titsias, M. K. & Williams, C. K. I., 2006, Toward Category-Level Object Recognition. Ponce, J., Hebert, M., Schmid, C. & Zisserman, A. (eds.). Springer Berlin Heidelberg, Vol. V. p. 577-595 19 p. (Lecture Notes in Computer Science; vol. 4170).

    Research output: Chapter in Book/Report/Conference proceedingChapter

  3. 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

  4. Stochastic modelling reveals mechanisms of metabolic heterogeneity

    Tonn, M., Thomas, P., Barahona, M. & Oyarzun, D., 21 Mar 2019, In : Communications biology. 2, 9 p., 108.

    Research output: Contribution to journalArticle

  5. Compiling and Optimizing for Decoupled Architectures

    Topham, N., Rawsthorne, A., McLean, C., Mewissen, M. & Bird, P., 1995, Supercomputing, 1995. Proceedings of the IEEE/ACM SC95 Conference. Institute of Electrical and Electronics Engineers (IEEE), p. 40-40 1 p.

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

  6. Probabilistic inference for solving discrete and continuous state Markov Decision Processes

    Toussaint, M. & Storkey, A., 2006, ICML '06 Proceedings of the 23rd international conference on Machine learning. ACM, p. 945-952 8 p.

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

  7. Probabilistic inference for solving (PO) MDPs

    Toussaint, M., Harmeling, S. & Storkey, A., Dec 2006, 22 p.

    Research output: Working paper

  8. Expectation-Maximization Methods for Solving (PO)MDPs and Optimal Control Problems.

    Toussaint, M., Storkey, A. J. & Harmeling, S., 2011, Bayesian Time Series Models. Chiappa, S. & Barber, D. (eds.). Cambridge University Press, p. 388-413 26 p.

    Research output: Chapter in Book/Report/Conference proceedingChapter

  9. Probabilistic Inference over RFID Streams in Mobile Environments

    Tran, T., Sutton, C., Cocci, R., Nie, Y., Diao, Y. & Shenoy, P., 2009, Data Engineering, 2009. ICDE '09. IEEE 25th International Conference on. Institute of Electrical and Electronics Engineers (IEEE), p. 1096-1107 12 p.

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

  10. Supporting User-Defined Functions on Uncertain Data

    Tran, T. T. L., Diao, Y., Sutton, C. A. & Liu, A., 2013, In : Proceedings of the VLDB Endowment (PVLDB). 6, 6, p. 469-480 12 p.

    Research output: Contribution to journalArticle