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Jiri Hron
Jiri Hron
Research Scientist, Google DeepMind
Verified email at google.com - Homepage
Title
Cited by
Cited by
Year
Concrete dropout
Y Gal, J Hron, A Kendall
NeurIPS, 2017
7122017
Gaussian process behaviour in wide deep neural networks
AGG Matthews, J Hron, M Rowland, RE Turner, Z Ghahramani
ICLR, 2018
556*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
3632019
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
2492020
Infinite attention: NNGP and NTK for deep attention networks
J Hron, Y Bahri, J Sohl-Dickstein, R Novak
ICML, 2020
1222020
Variational Bayesian dropout: pitfalls and fixes
J Hron, AGG Matthews, Z Ghahramani
ICML, 2018
812018
Successor Uncertainties: exploration and uncertainty in temporal difference learning
D Janz*, J Hron*, JM Hernández-Lobato, K Hofmann, S Tschiatschek
NeurIPS, 2019
662019
Variational Gaussian Dropout is not Bayesian
J Hron, AGG Matthews, Z Ghahramani
Bayesian Deep Learning (NeurIPS workshop), 2017
57*2017
Orthogonal Estimation of Wasserstein Distances
M Rowland*, J Hron*, Y Tang*, K Choromanski, T Sarlos, A Weller
AISTATS, 2019
472019
Beyond human data: Scaling self-training for problem-solving with language models
A Singh, JD Co-Reyes, R Agarwal, A Anand, P Patil, PJ Liu, J Harrison, ...
arXiv preprint arXiv:2312.06585, 2023
352023
Modeling content creator incentives on algorithm-curated platforms
J Hron*, K Krauth*, MI Jordan, N Kilbertus, S Dean
ICLR 2023, 2023
312023
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
302020
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
292017
On component interactions in two-stage recommender systems
J Hron, K Krauth, M Jordan, N Kilbertus
NeurIPS, 2021
262021
Exploration in two-stage recommender systems
J Hron*, K Krauth*, MI Jordan, N Kilbertus
REVEAL (ACM RecSys workshop), 2020
92020
Wide Bayesian neural networks have a simple weight posterior: theory and accelerated sampling
J Hron, R Novak, J Pennington, J Sohl-Dickstein
ICML, 2022
62022
The progression of disparities within the criminal justice system: Differential enforcement and risk assessment instruments
M Zilka, R Fogliato, J Hron, B Butcher, C Ashurst, A Weller
Proceedings of the 2023 ACM Conference on Fairness, Accountability, and …, 2023
42023
Optimising Human-Machine Collaboration for Efficient High-Precision Information Extraction from Text Documents
B Butcher, M Zilka, J Hron, D Cook, A Weller
ACM Journal on Responsible Computing 1 (2), 1-27, 2024
22024
Beyond Use-Cases: A Participatory Approach to Envisioning Data Science in Law Enforcement
C Kearney, J Hron, H Kosc, M Zilka
The 2024 ACM Conference on Fairness, Accountability, and Transparency, 1809-1826, 2024
2024
Scaling behaviour of neural networks: Existence and character of large width limits
J Hron
University of Cambridge, 2023
2023
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Articles 1–20