| Optimizing sequential experimental design with deep reinforcement learning T Blau, EV Bonilla, I Chades, A Dezfouli International conference on machine learning, 2107-2128, 2022 | 31 | 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 | 5 | 2020 |
| 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 |
| 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 | 2 | 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 |
| Cross-Entropy Estimators for Sequential Experiment Design with Reinforcement Learning T Blau, E Bonilla, I Chades, A Dezfouli arXiv preprint arXiv:2305.18435, 2023 | | 2023 |
| Hybrid Methods for Efficient Exploration in Reinforcement Learning T Blau University of Sydney, 2020 | | 2020 |
iadine ChadèsPrincipal Research Scientist CSIROVerified email at csiro.au
