Optimizing sequential experimental design with deep reinforcement learning T Blau, EV Bonilla, I Chades, A Dezfouli International conference on machine learning, 2107-2128, 2022 | 49 | 2022 |
Bayesian curiosity for efficient exploration in reinforcement learning T Blau, L Ott, F Ramos arXiv preprint arXiv:1911.08701, 2019 | 13 | 2019 |
Reinforcement learning with probabilistically complete exploration P Morere, G Francis, T Blau, F Ramos arXiv preprint arXiv:2001.06940, 2020 | 6 | 2020 |
Unsupervised machine learning framework for discriminating major variants of concern during COVID-19 R Chandra, C Bansal, M Kang, T Blau, V Agarwal, P Singh, LOW Wilson, ... Plos one 18 (5), e0285719, 2023 | 5 | 2023 |
Improving reinforcement learning pre-training with variational dropout T Blau, L Ott, F Ramos 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2018 | 5 | 2018 |
Cross-Entropy Estimators for Sequential Experiment Design with Reinforcement Learning T Blau, I Chades, A Dezfouli, DM Steinberg, EV Bonilla NeurIPS 2023 Workshop on Adaptive Experimental Design and Active Learning in …, 2023 | 3 | 2023 |
Learning from demonstration without demonstrations T Blau, P Morere, G Francis 2021 IEEE International Conference on Robotics and Automation (ICRA), 4116-4122, 2021 | 2 | 2021 |
Machine Learning for Biological Design T Blau, I Chades, CS Ong Synthetic Biology: Methods and Protocols, 319-344, 2024 | | 2024 |
Large language model for Bible sentiment analysis: Sermon on the Mount M Vora, T Blau, V Kachhwal, AMG Solo, R Chandra arXiv preprint arXiv:2401.00689, 2024 | | 2024 |
Statistically Efficient Bayesian Sequential Experiment Design via Reinforcement Learning with Cross-Entropy Estimators T Blau, I Chades, A Dezfouli, D Steinberg, EV Bonilla arXiv preprint arXiv:2305.18435, 2023 | | 2023 |
Hybrid Methods for Efficient Exploration in Reinforcement Learning T Blau University of Sydney, 2020 | | 2020 |