Edinburgh Research Explorer

Institute for Adaptive and Neural Computation

Organisational unit: Research Institute

  1. Functional imaging as a predictor of schizophrenia

    Whalley, H. C., Simonotto, E., Moorhead, W., McIntosh, A., Marshall, I., Ebmeier, K. P., Owens, D. G. C., Goddard, N. H., Johnstone, E. C. & Lawrie, S. M., 1 Sep 2006, In : Biological Psychiatry. 60, 5, p. 454-62 9 p.

    Research output: Contribution to journalArticle

  2. Assessing the validity of a learning analytics expectation instrument: A multinational study

    Whitelock-Wainwright, A., Gasevic, D., Tsai, Y-S., Drachsler, H., Scheffel, M., Muñoz-Merino, P., Tammets, K. & Delgado Kloos, C., 30 Apr 2020, In : Journal of Computer Assisted Learning. 36, 2, p. 209-240 32 p.

    Research output: Contribution to journalArticle

  3. Disciplinary Differences in Blended Learning Design: A Network Analytic Study

    Whitelock-Wainwright, A., Tsai, Y-S., Lyons, K., Khalif, S., Bryant, M., Ryan, K. & Gasevic, D., 23 Mar 2020, LAK '20: Proceedings of the Tenth International Conference on Learning Analytics & Knowledge. Association for Computing Machinery (ACM), p. 579-588 10 p.

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

  4. The Student Expectations of Learning Analytics Questionnaire (SELAQ)

    Whitelock-Wainwright, A., Gasevic, D., Tejeiro, R., Tsai, Y-S. & Bennett, K., Oct 2019, In : Journal of Computer Assisted Learning. 35, 5, p. 633-666 34 p.

    Research output: Contribution to journalArticle

  5. Event-related fMRI of word classification and successful word recognition in subjects at genetically enhanced risk of schizophrenia

    Whyte, M-C., Whalley, H. C., Simonotto, E., Flett, S., Shillcock, R., Marshall, I., Goddard, N. H., Johnstone, E. C. & Lawrie, S. M., Oct 2006, In : Psychological Medicine. 36, 10, p. 1427-39 13 p.

    Research output: Contribution to journalArticle

  6. Automating the Calibration of a Neonatal Condition Monitoring System

    Williams, C. K. I. & Stanculescu, I., 2011, Artificial Intelligence in Medicine: 13th Conference on Artificial Intelligence in Medicine, AIME 2011, Bled, Slovenia, July 2-6, 2011. Proceedings. Peleg, M., Lavrac, N. & Combi, C. (eds.). Springer-Verlag GmbH, p. 240-249 10 p. (Lecture Notes in Computer Science; vol. 6747).

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

  7. The effect of the input density distribution on kernel-based classifiers

    Williams, C. & Seeger, M., 2000, ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning. Morgan Kaufmann Publishers Inc., p. 1159-1166 8 p.

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

  8. Prediction With Gaussian Processes: From Linear Regression To Linear Prediction And Beyond

    Williams, C., 1997, Learning in Graphical Models. p. 599-621 23 p. (NATO ASI Series D: Behavioural and Social Sciences; vol. 89).

    Research output: Chapter in Book/Report/Conference proceedingChapter

  9. On a Connection between Kernel PCA and Metric Multidimensional Scaling

    Williams, C. K. I., Jan 2002, In : Machine Learning. 46, 1-3, p. 11-19 9 p.

    Research output: Contribution to journalArticle

  10. Cleaning astronomical databases using hough transforms and renewal strings

    Williams, CKI., Storkey, AJ., Hambly, NC. & Mann, RG., 2004, Advances in Scattering and Biomedical Engineering: Proceedings of the Sixth International Workshop. Fotiadis, DI. & Massalas, CV. (eds.). World Scientific, p. 439-452 14 p.

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

  11. Regression with Gaussian processes

    Williams, C. K. I., 1995, Mathematics of Neural Networks: Models, Algorithms and Applications. Springer US, p. 378-382 5 p. (Operations Research/Computer Science Interfaces Series; vol. 8).

    Research output: Chapter in Book/Report/Conference proceedingChapter

  12. Instantiating Deformable Models with a Neural Net

    Williams, C. K. I., Revow, M. & Hinton, G. E., Oct 1997, In : Computer Vision and Image Understanding. 68, 1, p. 120-126 7 p.

    Research output: Contribution to journalArticle

  13. On the extension of eigenvectors to new datapoints

    Williams, C. K. I., 2006, p. 1-3, 3 p.

    Research output: Working paper

  14. Extracting Motion Primitives from Natural Handwriting Data

    Williams, B. H., Toussaint, M. & Storkey, A. J., 2006, Artificial Neural Networks – ICANN 2006. Kollias, S., Stafylopatis, A., Duch, W. & Oja, E. (eds.). Springer-Verlag Berlin Heidelberg, p. 634-643 (Lecture Notes in Computer Science; vol. 4132).

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

  15. Computation With Infinite Neural Networks

    Williams, C. K. I., 1 Jul 1997, In : Neural Computation. 10, 5, p. 1203-1216 14 p.

    Research output: Contribution to journalArticle

  16. Bayesian Classification with Gaussian Processes

    Williams, C. K. I. & Barber, D., Dec 1998, In : IEEE Transactions on Pattern Analysis and Machine Intelligence. 20, 12, p. 1342-1351 10 p.

    Research output: Contribution to journalArticle

  17. How to pretend that correlated variables are independent by using difference observations

    Williams, C. K. I., Jan 2005, In : Neural Computation. 17, 1, p. 1-6 6 p.

    Research output: Contribution to journalArticle

  18. 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

  19. Observations on the Nyström Method for Gaussian Processes

    Williams, C. K. I., Rasmussen, C. E., Schwaighofer, A. & Tresp, V., 2002, 9 p.

    Research output: Working paper