38 citations · 81 across the 29 of their papers we have counts for
6 papers · 1 filter
Preference-based opponent shaping in differentiable games
Xinyu Qiao, Yudong Hu, Congying Han +2
Strategy learning in game environments with multi-agent is a challenging problem. Since each agent's reward is determined by the joint strategy, a greedy learning strategy that aim…
Mitigating Distribution Shift in Model-based Offline RL via Shifts-aware Reward Learning
Wang Luo, Haoran Li, Zicheng Zhang +4
Model-based offline reinforcement learning trains policies using pre-collected datasets and learned environment models, eliminating the need for direct real-world environment inter…
BlazeBVD: Make Scale-Time Equalization Great Again for Blind Video Deflickering
Xinmin Qiu, Congying Han, Zicheng Zhang +4
Developing blind video deflickering (BVD) algorithms to enhance video temporal consistency, is gaining importance amid the flourish of image processing and video generation. Howeve…
Learning Dynamic Tetrahedra for High-Quality Talking Head Synthesis
Zicheng Zhang, Ruobing Zheng, Ziwen Liu +7
Recent works in implicit representations, such as Neural Radiance Fields (NeRF), have advanced the generation of realistic and animatable head avatars from video sequences. These i…
Understanding Oversmoothing in Diffusion-Based GNNs From the Perspective of Operator Semigroup Theory
Weichen Zhao, Chenguang Wang, Xinyan Wang +3
This paper presents an analytical study of the oversmoothing issue in diffusion-based Graph Neural Networks (GNNs). Generalizing beyond extant approaches grounded in random walk an…
Towards Optimal Adversarial Robust Q-learning with Bellman Infinity-error
Haoran Li, Zicheng Zhang, Wang Luo +4
Establishing robust policies is essential to counter attacks or disturbances affecting deep reinforcement learning (DRL) agents. Recent studies explore state-adversarial robustness…