| Gaussian process classification of Alzheimer's disease and mild cognitive impairment from resting-state fMRI E Challis, P Hurley, L Serra, M Bozzali, S Oliver, M Cercignani NeuroImage 112, 232-243, 2015 | 203 | 2015 |
| Gaussian Kullback-Leibler Approximate Inference. E Challis, D Barber Journal of Machine Learning Research 14 (8), 2013 | 94 | 2013 |
| Fisher and Shannon information in finite neural populations S Yarrow, E Challis, P Seriès Neural computation 24 (7), 1740-1780, 2012 | 64 | 2012 |
| Concave Gaussian variational approximations for inference in large-scale Bayesian linear models E Challis, D Barber Proceedings of the Fourteenth International Conference on Artificial …, 2011 | 32 | 2011 |
| Affine independent variational inference E Challis, D Barber Advances in Neural Information Processing Systems 25, 2012 | 21 | 2012 |
| Measuring the accuracy of the neural code EAL Challis Master’s thesis, Informatics, University of Edinburgh, 2007 | 3 | 2007 |
| Fisher vs Shannon information in Populations of Neurons EAL Challis, S Yarrow, P Seriès Deuxième conférence française de Neurosciences Computationnelles," Neurocomp08", 2008 | 1 | 2008 |
| Generalized Multiple Intent Conditioned Slot Filling H Shah, A Wilcke, M Cobzarenco, C Cobzarenco, E Challis, D Barber arXiv preprint arXiv:2305.11023, 2023 | | 2023 |
| Variational Approximate Inference in Latent Linear Models EAL Challis UCL (University College London), 2013 | | 2013 |
| Fisher and Shannon Information in Finite Neural Populations S Yarrow, E Challis, P Series Neural Computation 24 (6), 1, 2011 | | 2011 |
| Affine Independent Variational Inference Supplementary Material E Challis, D Barber | | |
| Concave Gaussian Variational Approximations for Inference in Large-Scale Bayesian Linear Models: Supplementary Material E Challis, D Barber | | |
