Edinburgh Research Explorer

Institute for Adaptive and Neural Computation

Organisational unit: Research Institute

  1. Stochastic Parallel Block Coordinate Descent for Large-scale Saddle Point Problems

    Zhu, Z. & Storkey, A. J., Feb 2016, Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence. AAAI Press, p. 2429-2534 106 p. (AAAI'16).

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

  2. Blind source separation for fmri signals using spatial independent component analysis

    Zhong, M., Tang, H. & Tang, Y., Dec 2002, In : ACTA Biophysica Sinica. 19, 1, p. 79-83 5 p.

    Research output: Contribution to journalArticle

  3. Latent Bayesian melding for integrating individual and population models

    Zhong, M., Goddard, N. & Sutton, C., 2015, Advances in Neural Information Processing Systems 28 (NIPS 2015). p. 3617-3625 9 p.

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

  4. Signal Aggregate Constraints in Additive Factorial HMMs, with Application to Energy Disaggregation

    Zhong, M., Goddard, N. & Sutton, C., 2014, Advances in Neural Information Processing Systems 27 (NIPS 2014). Ghahramani, Z., Welling, M., Cortes, C., Lawrence, N. D. & Weinberger, K. Q. (eds.). Palais des Congrès de Montréal, Montréal, CANADA : Curran Associates Inc, p. 3590-3598 9 p.

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

  5. The Mathematical Principles of AFNI and One of its Applications to the Research of the Functional Neuroimages

    Zhong, M., Tang, H. & Feng, J., 2002, In : Journal of Basic Science and Engineering. 3, 4 p.

    Research output: Contribution to journalArticle

  6. 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

  7. Curve adaptation effects on high-level facial-expression judgments are predicted to have the same form as low-level aftereffects

    Zhao, C. R. & Bednar, J. A., 2010, In : Perception. 39, EVCP Abstract Supplement, p. 91-91 1 p.

    Research output: Contribution to journalMeeting abstract

  8. Modelling face adaptation aftereffects

    Zhao, C. R., Hancock, P. & Bednar, J. A., 2008.

    Research output: Contribution to conferencePoster

  9. Similar neural adaptation mechanisms underlying face gender and tilt aftereffects

    Zhao, C. R., Series, P., Hancock, P. J. B. & Bednar, J. A., Sep 2011, In : Vision Research. 51, 18, p. 2021-2030 10 p.

    Research output: Contribution to journalArticle

  10. Continuous Relaxations for Discrete Hamiltonian Monte Carlo

    Zhang, Y., Sutton, C. A., Storkey, A. J. & Ghahramani, Z., 2012, Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012, Lake Tahoe, Nevada, United States. MIT Press, p. 3203-3211 9 p.

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

  11. Quasi-Newton Methods for Markov Chain Monte Carlo

    Zhang, Y. & Sutton, C., 2011, Advances in Neural Information Processing Systems 24. Shawe-Taylor, J., Zemel, R. S., Bartlett, P., Pereira, F. C. N. & Weinberger, K. Q. (eds.). p. 2393-2401 9 p.

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

  12. Sequence-to-point learning with neural networks for non-intrusive load monitoring

    Zhang, C., Zhong, M., Wang, Z., Goddard, N. & Sutton, C., 7 Feb 2018, Proceedings for Thirty-Second AAAI Conference on Artificial Intelligence. New Orleans, Louisiana, USA: AAAI Press, p. 2604-2611 8 p.

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

  13. Semi-Separable Hamiltonian Monte Carlo for Inference in Bayesian Hierarchical Models

    Zhang, Y. & Sutton, C., 2014, Advances in Neural Information Processing Systems 27. Ghahramani, Z., Welling, M., Cortes, C., Lawrence, N. D. & Weinberger, K. Q. (eds.). Curran Associates Inc, p. 10-18 9 p.

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

  14. Directional-unit boltzmann machines

    Zemel, R. S., Williams, C. K. I. & Mozer, M. C., 1993, Advances in Neural Information Processing Systems 5. Morgan Kaufmann Publishers Inc., p. 172-179 8 p.

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

  15. Lending direction to neural networks

    Zemel, R. S., Williams, C. K. I. & Mozer, M. C., 1995, In : Neural Networks. 8, 4, p. 503-512 10 p.

    Research output: Contribution to journalArticle

  16. Individualized prediction of psychosis in subjects with an at-risk mental state

    Zarogianni, E., Storkey, A. J., Borgwardt, S., Smieskova, R., Studerus, E., Riecher-Rössler, A. & Lawrie, S. M., 19 Sep 2017, In : Schizophrenia Research.

    Research output: Contribution to journalArticle

  17. Point process modelling of the Afghan War Diary

    Zammit-Mangion, A., Dewar, M., Kadirkamanathan, V. & Sanguinetti, G., 2012, In : Proceedings of the National Academy of Sciences (PNAS). 109, 31, p. 12414-12419 6 p.

    Research output: Contribution to journalArticle

  18. Modeling Conflict Dynamics with Spatio-temporal Data

    Zammit-Mangion, A., Dewar, M., Kadirkamanathan, V., Flesken, A. & Sanguinetti, G., 2013, Springer International Publishing. 82 p. (Modeling Conflict Dynamics with Spatio-temporal Data)

    Research output: Book/ReportBook

  19. Variational Estimation in Spatiotemporal Systems From Continuous and Point-Process Observations

    Zammit-Mangion, A., Sanguinetti, G. & Kadirkamanathan, V., 1 Jul 2012, In : IEEE Transactions on Signal Processing. 60, 7, p. 3449-3459 11 p.

    Research output: Contribution to journalArticle

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