Edinburgh Research Explorer

Institute for Adaptive and Neural Computation

Organisational unit: Research Institute

  1. Conference contribution › Research
  2. Near-Optimal Machine Teaching via Explanatory Teaching Sets

    Chen, Y., Mac Aodha, O., Su, S., Perona, P. & Yue, Y., 1 Sep 2018, Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics. Storkey, A. & Perez-Cruz, F. (eds.). Playa Blanca, Lanzarote, Canary Islands: PMLR, Vol. 84. p. 1970-1978 9 p. (Proceedings of Machine Learning Research).

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

  3. Negentropy analysis of surface electromyogram signal

    Nazarpour, K., Sharafat, A. R. & Firoozabadi, S. M., 20 Jul 2005, IEEE/SP 13th Workshop on Statistical Signal Processing, 2005. Institute of Electrical and Electronics Engineers (IEEE), p. 974-977 4 p.

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

  4. Neighbourhood tractography: a new approach to seed point placement for fibre tracking

    Clayden, J. D., Bastin, M. & Storkey, A., 2006, Proceedings of the British Chapter of the ISMRM, Guildford, UK.

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

  5. Neonatal Learning of Faces: Environmental and Genetic Influences

    Bednar, J. A. & Miikkulainen, R., 2002, Proceedings of the 24th Annual Conference of the Cognitive Science Society. p. 107-112 6 p.

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

  6. Nested sampling for Potts models

    Murray, I., MacKay, D. J. C., Ghahramani, Z. & Skilling, J., 2006, Advances in Neural Information Processing Systems 18. Weiss, Y., Schölkopf, B. & Platt, J. (eds.). Cambridge, MA: MIT Press, p. 947-954 8 p.

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

  7. Neural Spline Flows

    Durkan, C., Bekasovs, A., Murray, I. & Papamakarios, G., 14 Dec 2019, Advances in Neural Information Processing Systems 32 (NeurIPS 2019). Curran Associates Inc, Vol. 32. p. 7509-7520 12 p.

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

  8. Neural network training using multi-channel data with aggregate labelling

    Bishop, C. M., Mcgrogan, N. & Tarassenko, L., 1999, Artificial Neural Networks, 1999. ICANN 99. Ninth International Conference on (Conf. Publ. No. 470). IET, p. 862-867 6 p.

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

  9. Neuronal Adaptation for Sampling-Based Probabilistic Inference in Perceptual Bistability

    Reichert, D. P., Series, P. & Storkey, A., 2011, Advances in Neural Information Processing Systems 24. Shawe-Taylor, J., Zemel, R. S., Bartlett, P. L., Pereira, F. & Weinberger, K. Q. (eds.). Curran Associates Inc

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

  10. Noise-contrastive estimation: A new estimation principle for unnormalized statistical models

    Gutmann, M. & Hyvärinen, A., 2010, Proceedings of the 13th International Conference on Artificial Intelligence and Statistics (AISTATS). Teh, Y. W. & Titterington, M. (eds.). Journal of Machine Learning Research - Proceedings Track, Vol. 9. p. 297-304 8 p. (JMLR WCP).

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

  11. Non-Gaussian probability distribution of the total transmission of multiply scattered light

    Boer, J. F. D., Van Rossum, M. C. W., Albada, M. P. V., Nieuwenhuizen, T. M. & Lagendijk, A., 1994, International Quantum Electronics Conference 1994. Optical Society of America (OSA), 1 p. QThE5

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