7 citations · 20 across the 22 of their papers we have counts for
Showing 2022Show all
2 papers · 1 filter
cs.LG2022★ 7 cited
PaCo: Parameter-Compositional Multi-Task Reinforcement Learning
Lingfeng Sun, Haichao Zhang, Wei Xu +1
The purpose of multi-task reinforcement learning (MTRL) is to train a single policy that can be applied to a set of different tasks. Sharing parameters allows us to take advantage…
cs.CV2022
PreTraM: Self-Supervised Pre-training via Connecting Trajectory and Map
Chenfeng Xu, Tian Li, Chen Tang +5
Deep learning has recently achieved significant progress in trajectory forecasting. However, the scarcity of trajectory data inhibits the data-hungry deep-learning models from lear…