Edinburgh Research Explorer

Institute for Adaptive and Neural Computation

Organisational unit: Research Institute

  1. Meeting abstract › Research › Peer-reviewed
  2. What can MaxEnt reveal about high-density recordings and what can high-density recordings reveal about MaxEnt?

    Panas, D., Maccione, A., Berdondini, L. & Hennig, M., 2011, In : BMC Neuroscience. 12, Supplement 1, 2 p., P146.

    Research output: Contribution to journalMeeting abstract

  3. Foreword/postscript › Research
  4. Dataset Shift in Machine Learning

    Shimodaira, H., Sugiyama, M., Storkey, A., Gretton, A., David, S-B., QuinoneroCandela, J., Sugiyama, M., Schwaighofer, A. & Lawrence, ND., 2009, DATASET SHIFT IN MACHINE LEARNING. CAMBRIDGE: Yale University Press in association with the Museum of London, p. 201-205 5 p. (Neural Information Processing Series).

    Research output: Chapter in Book/Report/Conference proceedingForeword/postscript

  5. Conference contribution › Research
  6. A Bayesian Network Model for Interesting Itemsets

    Fowkes, J. & Sutton, C., 4 Sep 2016, The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery (ECML-PKDD 2016). Riva del Garda, Italy: Springer, Cham, p. 410-425 16 p. (Lecture Notes in Computer Science ; vol. 9852).

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

  7. A CMOS Analog Front-End for Tunnelling Magnetoresistive Spintronic Sensing Systems

    Zuo, S., Fan, H., Nazarpour, K. & Heidari, H., 1 May 2019, 2019 IEEE International Symposium on Circuits and Systems (ISCAS). Institute of Electrical and Electronics Engineers (IEEE), p. 1-5 5 p.

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

  8. A Comparison of Frequentist and Bayesian Approaches to Latent Class Modelling of Susceptibility to Asthma and Patterns of Antibiotic Prescriptions in Early Life

    Belgrave, D., Bishop, C., Custovic, A., Simpson, A., Semic-Jusufagic, A., Pickles, A. & Buchan, I., 2011, Proceedings of the 26th International Workshop on Statistical Modelling. Valencia (Spain). p. 75-78 4 p.

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

  9. A Composable Strategy for Shredded Document Reconstruction

    Ranca, R. & Murray, I., 2013, Computer Analysis of Images and Patterns. Wilson, R., Hancock, E., Bors, A. & Smith, W. (eds.). Springer-Verlag GmbH, p. 324-331 8 p. (Lecture Notes in Computer Science; vol. 8048).

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

  10. A Convolutional Attention Network for Extreme Summarization of Source Code

    Allamanis, M., Peng, H. & Sutton, C., 24 Jun 2016, Proceedings of The 33rd International Conference on Machine Learning, PMLR. New York, United States: PMLR, Vol. 48. p. 2091-2100 10 p. (Proceedings of Machine Learning Research; vol. 48).

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

  11. A Deep and Tractable Density Estimator

    Uria, B., Murray, I. & Larochelle, H., 2014, Proceedings of The 31st International Conference on Machine Learning. Beijing, China: Journal of Machine Learning Research: Workshop and Conference Proceedings, Vol. 32. p. 467-475 9 p. (Journal of Machine Learning Research: Workshop and Conference Proceedings; vol. 32).

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

  12. A Family of Computationally Efficient and Simple Estimators for Unnormalized Statistical Models

    Pihlaja, M., Gutmann, M. & Hyvärinen, A., 2010, Proc. Conf. on Uncertainty in Artificial Intelligence (UAI). Corvallis, Oregon: AUAI Press, p. 442-449 8 p.

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

  13. A Framework for the Quantitative Evaluation of Disentangled Representations

    Eastwood, C. & Williams, C. K. I., 3 May 2018, Sixth International Conference on Learning Representations (ICLR 2018). 15 p.

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

  14. A Generative Model for Parts-based Object Segmentation

    Eslami, S. M. A. & Williams, C. K. I., 2012, Advances in Neural Information Processing Systems 25. Bartlett, P., Pereira, F. C. N., Burges, C. J. C., Bottou, L. & Weinberger, K. Q. (eds.). p. 100-107 8 p.

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

  15. A Hierarchical Generative Model of Recurrent Object-Based Attention in the Visual Cortex

    Reichert, D. P., Series, P. & Storkey, A. J., 2011, ARTIFICIAL NEURAL NETWORKS AND MACHINE LEARNING - ICANN 2011, PT I. Honkela, T., Duch, W., Girolami, M. & Kaski, S. (eds.). BERLIN: Springer-Verlag Berlin Heidelberg, p. 18-25 8 p. (Lecture Notes in Computer Science; vol. 6791).

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

  16. A Hierarchical Switching Linear Dynamical System Applied to the Detection of Sepsis in Neonatal Condition Monitoring

    Stanculescu, I., Williams, C. K. I. & Freer, Y., 2014, Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence (UAI 2014). 10 p.

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

  17. A Neural Network Approach to Tokamak Equilibrium Control

    Bishop, C., Cox, P., Haynes, P., Roach, C., Smith, M., Todd, T. & Trotman, D., 1992, Neural Network Applications. Taylor, J. G. (ed.). Springer London, p. 114-128 15 p. (Perspectives in Neural Computing).

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

  18. A Neural Network Model of Visual Tilt Aftereffects

    Bednar, J. A. & Miikkulainen, R., 1997, In Proceedings of the 19th Annual Conference of the Cognitive Science Society. Shafto, M. G. & Langley, P. (eds.). Erlbaum, p. 37-42 6 p.

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

  19. A New Framework for Machine Learning

    Bishop, C., 2008, Computational Intelligence: Research Frontiers: IEEE World Congress on Computational Intelligence, WCCI 2008, Hong Kong, China, June 1-6, 2008, Plenary/Invited Lectures. Zurada, J., Yen, G. & Wang, J. (eds.). Springer Berlin Heidelberg, p. 1-24 24 p. (Lecture Notes in Computer Science; vol. 5050).

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

  20. A New Probabilistic Generative Model of Parameter Inference in Biochemical Networks

    Lecca, P., Palmisano, A., Priami, C. & Sanguinetti, G., 2009, Proceedings of the 2009 ACM Symposium on Applied Computing. New York, NY, USA: ACM, p. 758-765 8 p. (SAC '09).

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

  21. A Novel Feature Extraction Scheme for Myoelectric Signals Classification Using Higher Order Statistics

    Nazarpour, K., Sharafat, A. R. & Firoozabadi, S. M., 18 Apr 2005, Conference Proceedings. 2nd International IEEE EMBS Conference on Neural Engineering, 2005.. Institute of Electrical and Electronics Engineers (IEEE), p. 293-296 4 p.

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

  22. A Novel Semi-Blind Signal Extraction Approach Incorporating Parafac for the Removal of Eye-Blink Artifact from EEGs

    Nazarpour, K., Sanei, S. & Chambers, J. A., 13 Aug 2007, 2007 15th International Conference on Digital Signal Processing. Institute of Electrical and Electronics Engineers (IEEE), p. 127-130 4 p.

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

  23. A Primitive Based Generative Model to Infer Timing Information in Unpartitioned Handwriting Data

    Williams, B. H., Toussaint, M. & Storkey, A. J., 2007, IJCAI 2007, Proceedings of the 20th International Joint Conference on Artificial Intelligence, Hyderabad, India, January 6-12, 2007. Veloso, MM. (ed.). Freiburg: IJCAI-INT JOINT CONF ARTIF INTELL, p. 1119-1124 6 p.

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

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