Hugh Salimbeni
Hugh Salimbeni
Verified email at ic.ac.uk - Homepage
Title
Cited by
Cited by
Year
Deep unsupervised clustering with gaussian mixture variational autoencoders
N Dilokthanakul, PAM Mediano, M Garnelo, MCH Lee, H Salimbeni, ...
arXiv preprint arXiv:1611.02648, 2016
3132016
Doubly stochastic variational inference for deep Gaussian processes
H Salimbeni, M Deisenroth
arXiv preprint arXiv:1705.08933, 2017
2082017
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
372018
Gaussian process conditional density estimation
V Dutordoir, H Salimbeni, M Deisenroth, J Hensman
arXiv preprint arXiv:1810.12750, 2018
272018
Deep Gaussian processes with importance-weighted variational inference
H Salimbeni, V Dutordoir, J Hensman, M Deisenroth
International Conference on Machine Learning, 5589-5598, 2019
192019
Orthogonally decoupled variational gaussian processes
H Salimbeni, CA Cheng, B Boots, M Deisenroth
arXiv preprint arXiv:1809.08820, 2018
192018
Deeply non-stationary Gaussian processes
H Salimbeni, MP Deisenroth
Proc. NIPS Workshop Bayesian Deep Learn., 2017
52017
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
52016
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
12020
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
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Articles 1–14