1 code implementation • 10 Mar 2023 • Amir Sadikov, Xinlei Pan, Hannah Choi, Lanya T. Cai, Pratik Mukherjee
Swin UNeTR enables rapid diffusion MRI with unprecedented accuracy and reliability, especially for probing biological tissues for scientific and clinical applications.
no code implementations • 21 Dec 2022 • Yiren Lu, Justin Fu, George Tucker, Xinlei Pan, Eli Bronstein, Rebecca Roelofs, Benjamin Sapp, Brandyn White, Aleksandra Faust, Shimon Whiteson, Dragomir Anguelov, Sergey Levine
To our knowledge, this is the first application of a combined imitation and reinforcement learning approach in autonomous driving that utilizes large amounts of real-world human driving data.
no code implementations • 19 Apr 2021 • Mingli Chen, Andreas Joseph, Michael Kumhof, Xinlei Pan, Xuan Zhou
We propose using deep reinforcement learning to solve dynamic stochastic general equilibrium models.
no code implementations • 22 Dec 2020 • Xinlei Pan, Animesh Garg, Animashree Anandkumar, Yuke Zhu
Through experimentation and comparative study, we demonstrate the effectiveness of our approach in discovering robust and cost-efficient hand morphologies for grasping novel objects.
no code implementations • 27 Sep 2019 • Xinlei Pan, Tingnan Zhang, Brian Ichter, Aleksandra Faust, Jie Tan, Sehoon Ha
Here, we propose a zero-shot imitation learning approach for training a visual navigation policy on legged robots from human (third-person perspective) demonstrations, enabling high-quality navigation and cost-effective data collection.
1 code implementation • 21 Jul 2019 • Xinlei Pan, Chaowei Xiao, Warren He, Shuang Yang, Jian Peng, MingJie Sun, JinFeng Yi, Zijiang Yang, Mingyan Liu, Bo Li, Dawn Song
To the best of our knowledge, we are the first to apply adversarial attacks on DRL systems to physical robots.
no code implementations • 24 Apr 2019 • Xinlei Pan, Wei-Yao Wang, Xiaoshuai Zhang, Bo Li, Jin-Feng Yi, Dawn Song
To the best of our knowledge, this is the first work to investigate privacy leakage in DRL settings and we show that DRL-based agents do potentially leak privacy-sensitive information from the trained policies.
no code implementations • 31 Mar 2019 • Xinlei Pan, Daniel Seita, Yang Gao, John Canny
In this paper we introduce risk-averse robust adversarial reinforcement learning (RARARL), using a risk-averse protagonist and a risk-seeking adversary.
no code implementations • 26 Aug 2018 • Xinlei Pan, Sung-Li Chiang, John Canny
First, we note that an optimal subset (relative to all the objects encountered and labeled) of labeled objects in images can be obtained by importance sampling using gradients of the recognition network.
no code implementations • 22 Jun 2018 • Xinlei Pan, Eshed Ohn-Bar, Nicholas Rhinehart, Yan Xu, Yilin Shen, Kris M. Kitani
The learning process is interactive, with a human expert first providing input in the form of full demonstrations along with some subgoal states.
6 code implementations • 13 Apr 2017 • Xinlei Pan, Yurong You, Ziyan Wang, Cewu Lu
To our knowledge, this is the first successful case of driving policy trained by reinforcement learning that can adapt to real world driving data.
no code implementations • 19 Oct 2016 • Daniel Seita, Xinlei Pan, Haoyu Chen, John Canny
We present a novel Metropolis-Hastings method for large datasets that uses small expected-size minibatches of data.