32 citations · 162 across the 19 of their papers we have counts for
6 papers · 1 filter
Informing Acquisition Functions via Foundation Models for Molecular Discovery
Qi Chen, Fabio Ramos, Alán Aspuru-Guzik +1
Bayesian Optimization (BO) is a key methodology for accelerating molecular discovery by estimating the mapping from molecules to their properties while seeking the optimal candidat…
Latent Skill Planning for Exploration and Transfer
Kevin Xie, Homanga Bharadhwaj, Danijar Hafner +2
To quickly solve new tasks in complex environments, intelligent agents need to build up reusable knowledge. For example, a learned world model captures knowledge about the environm…
Conservative Safety Critics for Exploration
Homanga Bharadhwaj, Aviral Kumar, Nicholas Rhinehart +3
Safe exploration presents a major challenge in reinforcement learning (RL): when active data collection requires deploying partially trained policies, we must ensure that these pol…
Continual Model-Based Reinforcement Learning with Hypernetworks
Yizhou Huang, Kevin Xie, Homanga Bharadhwaj +1
Effective planning in model-based reinforcement learning (MBRL) and model-predictive control (MPC) relies on the accuracy of the learned dynamics model. In many instances of MBRL a…
Model-Predictive Control via Cross-Entropy and Gradient-Based Optimization
Homanga Bharadhwaj, Kevin Xie, Florian Shkurti
Recent works in high-dimensional model-predictive control and model-based reinforcement learning with learned dynamics and reward models have resorted to population-based optimizat…
Diversity inducing Information Bottleneck in Model Ensembles
Samarth Sinha, Homanga Bharadhwaj, Anirudh Goyal +3
Although deep learning models have achieved state-of-the-art performance on a number of vision tasks, generalization over high dimensional multi-modal data, and reliable predictive…