| Ensemble sampling X Lu, B Van Roy Advances in neural information processing systems 30, 2017 | 93 | 2017 |
| Reinforcement learning, bit by bit X Lu, B Van Roy, V Dwaracherla, M Ibrahimi, I Osband, Z Wen arXiv preprint arXiv:2103.04047, 2021 | 33 | 2021 |
| Information-theoretic confidence bounds for reinforcement learning X Lu, B Van Roy Advances in Neural Information Processing Systems 32, 2019 | 30 | 2019 |
| Hypermodels for exploration V Dwaracherla, X Lu, M Ibrahimi, I Osband, Z Wen, B Van Roy International Conference on Learning Representations, 2020 | 28 | 2020 |
| Epistemic neural networks I Osband, Z Wen, SM Asghari, V Dwaracherla, M Ibrahimi, X Lu, ... arXiv preprint arXiv:2107.08924, 2021 | 26 | 2021 |
| Efficient online recommendation via low-rank ensemble sampling X Lu, Z Wen, B Kveton Proceedings of the 12th ACM Conference on Recommender Systems, 460-464, 2018 | 13 | 2018 |
| Evaluating Predictive Distributions: Does Bayesian Deep Learning Work? I Osband, Z Wen, SM Asghari, X Lu, M Ibrahimi, V Dwaracherla, ... | 6 | 2021 |
| From predictions to decisions: The importance of joint predictive distributions Z Wen, I Osband, C Qin, X Lu, M Ibrahimi, V Dwaracherla, M Asghari, ... arXiv preprint arXiv:2107.09224, 2021 | 5 | 2021 |
| Evaluating High-Order Predictive Distributions in Deep Learning I Osband, Z Wen, SM Asghari, V Dwaracherla, X Lu, B Van Roy The 38th Conference on Uncertainty in Artificial Intelligence, 2022 | 4 | 2022 |
| The Neural Testbed: Evaluating Joint Predictions I Osband, Z Wen, SM Asghari, V Dwaracherla, B Hao, M Ibrahimi, ... arXiv preprint arXiv:2110.04629, 2021 | 3 | 2021 |
| Information-directed sampling for reinforcement learning X Lu Stanford University, 2020 | 3 | 2020 |
| An analysis of ensemble sampling C Qin, Z Wen, X Lu, B Van Roy arXiv preprint arXiv:2203.01303, 2022 | 2 | 2022 |
| Ensembles for Uncertainty Estimation: Benefits of Prior Functions and Bootstrapping V Dwaracherla, Z Wen, I Osband, X Lu, SM Asghari, B Van Roy arXiv preprint arXiv:2206.03633, 2022 | 1 | 2022 |
| Evaluating probabilistic inference in deep learning: Beyond marginal predictions X Lu, I Osband, B Van Roy, Z Wen arXiv e-prints, arXiv: 2107.09224, 2021 | 1 | 2021 |
| Exploration using hyper-models B Van Roy, X Lu, VR Dwaracherla, Z Wen, M Ibrahimi, IDM Osband US Patent App. 17/639,504, 2022 | | 2022 |
| Robustness of Epinets against Distributional Shifts X Lu, I Osband, SM Asghari, S Gowal, V Dwaracherla, Z Wen, B Van Roy arXiv preprint arXiv:2207.00137, 2022 | | 2022 |
