Jiri Hron
Jiri Hron
Verified email at cam.ac.uk - Homepage
Cited by
Cited by
Concrete dropout
Y Gal, J Hron, A Kendall
NeurIIPS 2017, 2017
Gaussian process behaviour in wide deep neural networks
AGG Matthews, J Hron, M Rowland, RE Turner, Z Ghahramani
ICLR 2018, 2018
Bayesian Deep Convolutional Networks with Many Channels are Gaussian Processes
R Novak, L Xiao, Y Bahri, J Lee, G Yang, J Hron, DA Abolafia, ...
ICLR 2019, 2019
Neural Tangents: Fast and Easy Infinite Neural Networks in Python
R Novak, L Xiao, J Hron, J Lee, AA Alemi, J Sohl-Dickstein, ...
ICLR 2020, 2020
Variational Bayesian dropout: pitfalls and fixes
J Hron, AGG Matthews, Z Ghahramani
ICML 2018, 2018
Variational Gaussian Dropout is not Bayesian
J Hron, AGG Matthews, Z Ghahramani
Bayesian Deep Learning workshop (NeurIPS 2017), 2017
Successor Uncertainties: exploration and uncertainty in temporal difference learning
D Janz*, J Hron*, JM Hernández-Lobato, K Hofmann, S Tschiatschek
NeurIPS 2019, 2019
Orthogonal Estimation of Wasserstein Distances
M Rowland*, J Hron*, Y Tang*, K Choromanski, T Sarlos, A Weller
AISTATS 2019, 2019
Sample-then-optimize posterior sampling for Bayesian linear models
AGG Matthews, J Hron, RE Turner, Z Ghahramani
Advances in Approximate Bayesian Inference workshop (NeurIPS 2017), 2017
Infinite attention: NNGP and NTK for deep attention networks
J Hron, Y Bahri, J Sohl-Dickstein, R Novak
ICML 2020, 2020
Exploration in two-stage recommender systems
J Hron*, K Krauth*, MI Jordan, N Kilbertus
arXiv preprint arXiv:2009.08956, 2020
Exact posterior distributions of wide Bayesian neural networks
J Hron, Y Bahri, R Novak, J Pennington, J Sohl-Dickstein
arXiv preprint arXiv:2006.10541, 2020
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Articles 1–12