1 citations · 1 across the 8 of their papers we have counts for
8 papers
Provably and Practically Efficient Adversarial Imitation Learning with General Function Approximation
Tian Xu, Zhilong Zhang, Ruishuo Chen +2
As a prominent category of imitation learning methods, adversarial imitation learning (AIL) has garnered significant practical success powered by neural network approximation. Howe…
Singular Solutions for the Conformal Dirac-Einstein Problem on the Sphere
Ali Maalaoui, Vittorio Martino, Tian Xu
In this paper we investigate the existence of singular solutions to the conformal Dirac-Einstein system. Because of its conformal invariance, there are many similarities with the c…
Reward-Consistent Dynamics Models are Strongly Generalizable for Offline Reinforcement Learning
Fan-Ming Luo, Tian Xu, Xingchen Cao +1
Learning a precise dynamics model can be crucial for offline reinforcement learning, which, unfortunately, has been found to be quite challenging. Dynamics models that are learned…
Provably Efficient Adversarial Imitation Learning with Unknown Transitions
Tian Xu, Ziniu Li, Yang Yu +1
Imitation learning (IL) has proven to be an effective method for learning good policies from expert demonstrations. Adversarial imitation learning (AIL), a subset of IL methods, is…
Non-compactness results for the spinorial Yamabe-type problems with non-smooth geometric data
Takeshi Isobe, Yannick Sire, Tian Xu
Let be an -dimensional closed spin manifold, with a fixed Riemannian metric and a fixed spin structure ; let be the spinor bun…
Solutions of Spinorial Yamabe-type Problems on : Perturbations and Applications
Takeshi Isobe, Tian Xu
This paper is part of a program to establish the existence theory for the conformally invariant Dirac equation \[ D_{\textit{g}}ψ=f(x)|ψ|_{\textit{g}}^{\frac2{m-1}}ψ\] on a closed…