| Concrete dropout Y Gal, J Hron, A Kendall NeurIPS, 2017 | 644 | 2017 |
| Gaussian process behaviour in wide deep neural networks AGG Matthews, J Hron, M Rowland, RE Turner, Z Ghahramani ICLR, 2018 | 491* | 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 | 315 | 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 | 220 | 2020 |
| Infinite attention: NNGP and NTK for deep attention networks J Hron, Y Bahri, J Sohl-Dickstein, R Novak ICML, 2020 | 97 | 2020 |
| Variational Bayesian dropout: pitfalls and fixes J Hron, AGG Matthews, Z Ghahramani ICML, 2018 | 76 | 2018 |
| Successor Uncertainties: exploration and uncertainty in temporal difference learning D Janz*, J Hron*, JM Hernández-Lobato, K Hofmann, S Tschiatschek NeurIPS, 2019 | 53 | 2019 |
| Variational Gaussian Dropout is not Bayesian J Hron, AGG Matthews, Z Ghahramani Bayesian Deep Learning (NeurIPS workshop), 2017 | 50* | 2017 |
| Orthogonal Estimation of Wasserstein Distances M Rowland*, J Hron*, Y Tang*, K Choromanski, T Sarlos, A Weller AISTATS, 2019 | 42 | 2019 |
| 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 | 26 | 2020 |
| 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 | 26 | 2017 |
| On component interactions in two-stage recommender systems J Hron, K Krauth, M Jordan, N Kilbertus NeurIPS, 2021 | 23 | 2021 |
| Modeling content creator incentives on algorithm-curated platforms J Hron*, K Krauth*, MI Jordan, N Kilbertus, S Dean ICLR 2023, 2023 | 12 | 2023 |
| Exploration in two-stage recommender systems J Hron*, K Krauth*, MI Jordan, N Kilbertus REVEAL (ACM RecSys workshop), 2020 | 8 | 2020 |
| Wide Bayesian neural networks have a simple weight posterior: theory and accelerated sampling J Hron, R Novak, J Pennington, J Sohl-Dickstein ICML, 2022 | 4 | 2022 |
| Optimising Human-Machine Collaboration for Efficient High-Precision Information Extraction from Text Documents B Butcher, M Zilka, D Cook, J Hron, A Weller arXiv preprint arXiv:2302.09324, 2023 | 2 | 2023 |
| 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 | | 2023 |
| Scaling behaviour of neural networks: Existence and character of large width limits J Hron University of Cambridge, 2023 | | 2023 |
Alexander G. D. G. MatthewsDeepMindVerified email at google.com
