
![]() Deep Interactive Bayesian Reinforcement Learning via Meta-LearningAdaptive Agents and Multi-Agent Systems (AAMAS), 2021 |
![]() Towards Continual Reinforcement Learning: A Review and PerspectivesJournal of Artificial Intelligence Research (JAIR), 2020 |
![]() Meta-learning in natural and artificial intelligenceCurrent Opinion in Behavioral Sciences (Curr Opin Behav Sci), 2020 |
![]() Few-shot model-based adaptation in noisy conditionsIEEE Robotics and Automation Letters (RA-L), 2020 |
![]() Learning Not to Learn: Nature versus Nurture in SilicoAAAI Conference on Artificial Intelligence (AAAI), 2020 |
![]() Exploration in Approximate Hyper-State Space for Meta Reinforcement
LearningInternational Conference on Machine Learning (ICML), 2020 |
![]() The Synthesizability of Molecules Proposed by Generative ModelsJournal of Chemical Information and Modeling (JCIM), 2020 Wenhao Gao Connor W. Coley |
![]() Bayesian Residual Policy Optimization: Scalable Bayesian Reinforcement
Learning with Clairvoyant ExpertsIEEE/RJS International Conference on Intelligent RObots and Systems (IROS), 2020 |
![]() VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-LearningInternational Conference on Learning Representations (ICLR), 2019 |
![]() Gated Linear NetworksAAAI Conference on Artificial Intelligence (AAAI), 2019 |
![]() Towards Finding Longer ProofsInternational Conference on Theorem Proving with Analytic Tableaux and Related Methods (TABLEAUX), 2019 |