Deep unsupervised clustering with gaussian mixture variational autoencoders N Dilokthanakul, PAM Mediano, M Garnelo, MCH Lee, H Salimbeni, ... arXiv preprint arXiv:1611.02648, 2016 | 313 | 2016 |
Doubly stochastic variational inference for deep Gaussian processes H Salimbeni, M Deisenroth arXiv preprint arXiv:1705.08933, 2017 | 208 | 2017 |
Natural Gradients in Practice: Non-Conjugate Variational Inference in Gaussian Process Models H Salimbeni, S Eleftheriadis, J Hensman International Conference on Artificial Intelligence and Statistics, 2018 | 37 | 2018 |
Gaussian process conditional density estimation V Dutordoir, H Salimbeni, M Deisenroth, J Hensman arXiv preprint arXiv:1810.12750, 2018 | 27 | 2018 |
Deep Gaussian processes with importance-weighted variational inference H Salimbeni, V Dutordoir, J Hensman, M Deisenroth International Conference on Machine Learning, 5589-5598, 2019 | 19 | 2019 |
Orthogonally decoupled variational gaussian processes H Salimbeni, CA Cheng, B Boots, M Deisenroth arXiv preprint arXiv:1809.08820, 2018 | 19 | 2018 |
Deeply non-stationary Gaussian processes H Salimbeni, MP Deisenroth Proc. NIPS Workshop Bayesian Deep Learn., 2017 | 5 | 2017 |
Deep unsupervised clustering with Gaussian mixture variational autoencoders. arXiv N Dilokthanakul, PAM Mediano, M Garnelo, MCH Lee, H Salimbeni, ... arXiv preprint arXiv:1611.02648, 2016 | 5 | 2016 |
A potential biomarker for treatment stratification in psychosis: evaluation of an [18 F] FDOPA PET imaging approach M Veronese, B Santangelo, S Jauhar, E D’Ambrosio, A Demjaha, ... Neuropsychopharmacology, 1-11, 2020 | 1 | 2020 |
Stochastic Differential Equations with Variational Wishart Diffusions M Jørgensen, M Deisenroth, H Salimbeni International Conference on Machine Learning, 4974-4983, 2020 | | 2020 |
Machine learning system S Eleftheriadis, J Hensman, S John, H Salimbeni US Patent App. 16/824,025, 2020 | | 2020 |
Deep Gaussian Processes: Advances in Models and Inference H Salimbeni Imperial College London, 2019 | | 2019 |
Doubly Stochastic Inference for Deep Gaussian Processes H Salimbeni | | |
Patch kernels for Gaussian processes in high-dimensional imaging problems MCH Lee, H Salimbeni, MP Deisenroth, B Glocker | | |