Molecular machine learning bears promise for efficient molecular property prediction and
drug discovery. However, labelled molecule data can be expensive and time consuming to …

Deep reinforcement learning (DRL) has shown remarkable capabilities in solving sequential
decision-making problems. However, DRL requires extensive interactions with image-based …

Imitation learning, and robot learning in general, emerged due to breakthroughs in machine
learning, rather than breakthroughs in robotics. As such, evaluation metrics for robot …

Due to their ability to adapt to different terrains, quadruped robots have drawn much
attention in the research field of robot learning. Legged mobile manipulation, where a …

Semantically connecting users and items is a fundamental problem for the matching stage of
an industrial recommender system. Recent advances in this topic are based on multi …

Deep learning (DL) has been widely implemented in molecular modeling for property
predictions. However, there are two major challenges in DL for molecules.(1) The chemical …