Edinburgh Research Explorer

Institute for Adaptive and Neural Computation

Organisational unit: Research Institute

  1. Adaptation of anaerobic cultures of Escherichia coli K-12 in response to environmental trimethylamine-N-oxide

    Denby, K. J., Rolfe, M. D., Crick, E., Sanguinetti, G., Poole, R. K. & Green, J., Jul 2015, In : Environmental Microbiology. 17, 7, p. 2477-2491 15 p.

    Research output: Contribution to journalArticle

  2. Adapting proportional myoelectric-controlled interfaces for prosthetic hands

    Pistohl, T., Cipriani, C., Jackson, A. & Nazarpour, K., 26 Sep 2013, 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). Institute of Electrical and Electronics Engineers (IEEE), p. 6195-6198 4 p.

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

  3. Adaptive Approximate Bayesian Computation Tolerance Selection

    Simola, U., Cisewski-Kehe, J., Gutmann, M. U. & Corander, J., 7 May 2020, In : Bayesian analysis. 27 p.

    Research output: Contribution to journalArticle

  4. Adaptive Gaussian Copula ABC

    Chen, Y. & Gutmann, M., 25 Apr 2019, Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics (AISTATS 2019). Naha, Okinawa, Japan: PMLR, Vol. 89. p. 1584-1592 14 p. (Proceedings of Machine Learning Research; vol. 89).

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

  5. Adaptive Stochastic Primal-Dual Coordinate Descent for Separable Saddle Point Problems

    Zhu, Z. & Storkey, A., 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. 645-658 14 p. (Lecture Notes in Computer Science; vol. 9284).

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

  6. Adaptive elastic models for hand-printed character recognition

    Hinton, G. E., Williams, C. K. I. & Revow, M. D., 1991, Advances in Neural Information Processing Systems 4 (NIPS 1991). MIT Press, p. 512-519 8 p.

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

  7. Adaptive integration in the visual cortex by depressing recurrent cortical circuits

    van Rossum, M. C. W., van der Meer, M., Xiao, D. K. & Oram, M. W., Jul 2008, In : Neural Computation. 20, 7, p. 1847-1872 26 p.

    Research output: Contribution to journalArticle

  8. Adaptive thresholding for reliable topological inference in single subject fMRI analysis

    Gorgolewski, K. J., Storkey, A. J., Bastin, M. E. & Pernet, C. R., 25 Aug 2012, In : Frontiers in Human Neuroscience. 6, 245.

    Research output: Contribution to journalArticle

  9. Adding Constrained Discontinuities to Gaussian Process Models of Wind Fields

    Cornford, D., Nabney, I. T. & Williams, C. K. I., 1998, Advances in Neural Information Processing Systems 11 (NIPS 1998). p. 861-867 7 p.

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

  10. Advances in electroencephalography signal processing

    Sanei, S., Ferdowsi, S., Nazarpour, K. & Cichocki, A., 1 Jan 2013, In : IEEE Signal Processing Magazine. 30, 1, p. 170 - 176 7 p.

    Research output: Contribution to journalArticle

  11. Age-dependent Homeostatic Plasticity of GABAergic Signaling in Developing Retinal Networks

    Hennig, M., Grady, J., van Coppenhagen, J. & Sernagor, E., 24 Aug 2011, In : The Journal of Neuroscience. 31, 34, p. 12159-12164 6 p.

    Research output: Contribution to journalArticle

  12. 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

  13. 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 (PNAS). 113, 28, p. E4025-E4034 10 p.

    Research output: Contribution to journalArticle

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

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

    Research output: Contribution to conferencePaper

  15. 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

  16. 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

  17. 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

  18. 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)

Previous 1...3 4 5 6 7 8 9 10 ...74 Next