18 citations · 51 across the 9 of their papers we have counts for
9 papers
Bridging State and History Representations: Understanding Self-Predictive RL
Tianwei Ni, Benjamin Eysenbach, Erfan Seyedsalehi +4
Representations are at the core of all deep reinforcement learning (RL) methods for both Markov decision processes (MDPs) and partially observable Markov decision processes (POMDPs…
When Do Transformers Shine in RL? Decoupling Memory from Credit Assignment
Tianwei Ni, Michel Ma, Benjamin Eysenbach +1
Reinforcement learning (RL) algorithms face two distinct challenges: learning effective representations of past and present observations, and determining how actions influence futu…
Towards Disturbance-Free Visual Mobile Manipulation
Tianwei Ni, Kiana Ehsani, Luca Weihs +1
Deep reinforcement learning has shown promising results on an abundance of robotic tasks in simulation, including visual navigation and manipulation. Prior work generally aims to b…
Recurrent Model-Free RL Can Be a Strong Baseline for Many POMDPs
Tianwei Ni, Benjamin Eysenbach, Ruslan Salakhutdinov
Many problems in RL, such as meta-RL, robust RL, generalization in RL, and temporal credit assignment, can be cast as POMDPs. In theory, simply augmenting model-free RL with memory…
Adaptive Agent Architecture for Real-time Human-Agent Teaming
Tianwei Ni, Huao Li, Siddharth Agrawal +6
Teamwork is a set of interrelated reasoning, actions and behaviors of team members that facilitate common objectives. Teamwork theory and experiments have resulted in a set of stat…
f-IRL: Inverse Reinforcement Learning via State Marginal Matching
Tianwei Ni, Harshit Sikchi, Yufei Wang +3
Imitation learning is well-suited for robotic tasks where it is difficult to directly program the behavior or specify a cost for optimal control. In this work, we propose a method…
Meta-SAC: Auto-tune the Entropy Temperature of Soft Actor-Critic via Metagradient
Yufei Wang, Tianwei Ni
Exploration-exploitation dilemma has long been a crucial issue in reinforcement learning. In this paper, we propose a new approach to automatically balance between these two. Our m…
Elastic Boundary Projection for 3D Medical Image Segmentation
Tianwei Ni, Lingxi Xie, Huangjie Zheng +2
We focus on an important yet challenging problem: using a 2D deep network to deal with 3D segmentation for medical image analysis. Existing approaches either applied multi-view pla…
Phase Collaborative Network for Two-Phase Medical Image Segmentation
Huangjie Zheng, Lingxi Xie, Tianwei Ni +5
In real-world practice, medical images acquired in different phases possess complementary information, {\em e.g.}, radiologists often refer to both arterial and venous scans in ord…