4 papers · 1 filter
Max-Sliced Wasserstein Distance and its use for GANs
Ishan Deshpande, Yuan-Ting Hu, Ruoyu Sun +6
Generative adversarial nets (GANs) and variational auto-encoders have significantly improved our distribution modeling capabilities, showing promise for dataset augmentation, image…
Reinforcement Learning Gradients as Vitamin for Online Finetuning Decision Transformers
Kai Yan, Alexander G. Schwing, Yu-Xiong Wang
Decision Transformers have recently emerged as a new and compelling paradigm for offline Reinforcement Learning (RL), completing a trajectory in an autoregressive way. While improv…
Robust Model-Based Optimization for Challenging Fitness Landscapes
Saba Ghaffari, Ehsan Saleh, Alexander G. Schwing +3
Protein design, a grand challenge of the day, involves optimization on a fitness landscape, and leading methods adopt a model-based approach where a model is trained on a training…
Offline Imitation from Observation via Primal Wasserstein State Occupancy Matching
Kai Yan, Alexander G. Schwing, Yu-xiong Wang
In real-world scenarios, arbitrary interactions with the environment can often be costly, and actions of expert demonstrations are not always available. To reduce the need for both…