21 citations · 23 across the 2 of their papers we have counts for
3 papers
cs.LG2022★ 2 cited
Robust Imitation Learning from Corrupted Demonstrations
Liu Liu, Ziyang Tang, Lanqing Li +1
We consider offline Imitation Learning from corrupted demonstrations where a constant fraction of data can be noise or even arbitrary outliers. Classical approaches such as Behavio…
cs.LG2022★ 21 cited
DrugOOD: Out-of-Distribution (OOD) Dataset Curator and Benchmark for AI-aided Drug Discovery -- A Focus on Affinity Prediction Problems with Noise Annotations
Yuanfeng Ji, Lu Zhang, Jiaxiang Wu +16
AI-aided drug discovery (AIDD) is gaining increasing popularity due to its promise of making the search for new pharmaceuticals quicker, cheaper and more efficient. In spite of its…
cs.LG2021
Provably Improved Context-Based Offline Meta-RL with Attention and Contrastive Learning
Lanqing Li, Yuanhao Huang, Mingzhe Chen +3
Meta-learning for offline reinforcement learning (OMRL) is an understudied problem with tremendous potential impact by enabling RL algorithms in many real-world applications. A pop…