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Jiri Hron
Jiri Hron
PhD student, University of Cambridge
Zweryfikowany adres z cam.ac.uk - Strona główna
Tytuł
Cytowane przez
Cytowane przez
Rok
Concrete dropout
Y Gal, J Hron, A Kendall
NeurIPS, 2017
5342017
Gaussian process behaviour in wide deep neural networks
AGG Matthews, J Hron, M Rowland, RE Turner, Z Ghahramani
ICLR, 2018
410*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
2512019
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
1722020
Variational Bayesian dropout: pitfalls and fixes
J Hron, AGG Matthews, Z Ghahramani
ICML, 2018
652018
Infinite attention: NNGP and NTK for deep attention networks
J Hron, Y Bahri, J Sohl-Dickstein, R Novak
ICML, 2020
572020
Successor Uncertainties: exploration and uncertainty in temporal difference learning
D Janz*, J Hron*, JM Hernández-Lobato, K Hofmann, S Tschiatschek
NeurIPS, 2019
412019
Variational Gaussian Dropout is not Bayesian
J Hron, AGG Matthews, Z Ghahramani
Bayesian Deep Learning (NeurIPS workshop), 2017
41*2017
Orthogonal Estimation of Wasserstein Distances
M Rowland*, J Hron*, Y Tang*, K Choromanski, T Sarlos, A Weller
AISTATS, 2019
302019
Exact posterior distributions of wide Bayesian neural networks
J Hron, Y Bahri, R Novak, J Pennington, J Sohl-Dickstein
Uncertainty in Deep Learning (ICML workshop), 2020
172020
Sample-then-optimize posterior sampling for Bayesian linear models
AGG Matthews, J Hron, RE Turner, Z Ghahramani
Advances in Approximate Bayesian Inference (NeurIPS workshop), 2017
17*2017
On component interactions in two-stage recommender systems
J Hron, K Krauth, M Jordan, N Kilbertus
NeurIPS, 2021
112021
Exploration in two-stage recommender systems
J Hron*, K Krauth*, MI Jordan, N Kilbertus
REVEAL (ACM RecSys workshop), 2020
62020
Modeling content creator incentives on algorithm-curated platforms
J Hron*, K Krauth*, MI Jordan, N Kilbertus, S Dean
arXiv preprint arXiv:2206.13102, 2022
32022
Wide Bayesian neural networks have a simple weight posterior: theory and accelerated sampling
J Hron, R Novak, J Pennington, J Sohl-Dickstein
ICML, 2022
12022
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