Phase Collaborative Network for Multi-Phase Medical Imaging Segmentation. - Huangjie Zheng; Lingxi Xie; Tianwei Ni; Ya Zhang 002; Yanfeng Wang 001; Qi Tian 001; Elliot K. Fishman; Alan L. Yuille (CoRR, 2018)

Elastic Boundary Projection for 3D Medical Imaging Segmentation. - Tianwei Ni; Lingxi Xie; Huangjie Zheng; Elliot K. Fishman; Alan L. Yuille (CoRR, 2018)

Elastic Boundary Projection for 3D Medical Image Segmentation. - Tianwei Ni; Lingxi Xie; Huangjie Zheng; Elliot K. Fishman; Alan L. Yuille (CVPR, 2019)

f-IRL: Inverse Reinforcement Learning via State Marginal Matching. - Tianwei Ni; Harshit S. Sikchi; Yufei Wang; Tejus Gupta; Lisa Lee; Ben Eysenbach (CoRL, 2020)

Lightweight Convolutional Neural Networks for Vehicle Target Recognition. - Jintao Wang; Ping Ji; Wen Xiao; Tianwei Ni; Wei Sun; Sheng Zeng (ICITE, 2020)

Meta-SAC: Auto-tune the Entropy Temperature of Soft Actor-Critic via Metagradient. - Yufei Wang; Tianwei Ni (CoRR, 2020)

Adaptive Agent Architecture for Real-time Human-Agent Teaming. - Tianwei Ni; Huao Li; Siddharth Agrawal; Suhas Raja; Fan Jia; Yikang Gui; Dana Hughes 001; Michael Lewis 001; Katia P. Sycara (CoRR, 2021)

Recurrent Model-Free RL is a Strong Baseline for Many POMDPs. - Tianwei Ni; Benjamin Eysenbach; Ruslan Salakhutdinov (CoRR, 2021)

Individualized Mutual Adaptation in Human-Agent Teams. - Huao Li; Tianwei Ni; Siddharth Agrawal; Fan Jia; Suhas Raja; Yikang Gui; Dana Hughes 001; Michael Lewis 001; Katia P. Sycara (IEEE Trans. Hum. Mach. Syst., 2021)

Recurrent Model-Free RL Can Be a Strong Baseline for Many POMDPs. - Tianwei Ni; Benjamin Eysenbach; Ruslan Salakhutdinov (ICML, 2022)

When Do Transformers Shine in RL? Decoupling Memory from Credit Assignment. - Tianwei Ni; Michel Ma; Benjamin Eysenbach; Pierre-Luc Bacon (NeurIPS, 2023)

Towards Disturbance-Free Visual Mobile Manipulation. - Tianwei Ni; Kiana Ehsani; Luca Weihs; Jordi Salvador (WACV, 2023)

Genetic Quantization-Aware Approximation for Non-Linear Operations in Transformers. - Pingcheng Dong; Yonghao Tan; Dong Zhang; Tianwei Ni; Xuejiao Liu; Yu Liu 007; Peng Luo; Luhong Liang; Shih-Yang Liu; Xijie Huang; Huaiyu Zhu 004; Yun Pan; et al. (DAC, 2024)

AESHA: Accelerating Eigen-decomposition-based Sparse Transformer with Hybrid RRAM-SRAM Architecture. - Xuliang Yu; Tianwei Ni; Xinsong Sheng; Yun Pan; Lei He 001; Liang Zhao (ICCAD, 2024)

Bridging State and History Representations: Understanding Self-Predictive RL. - Tianwei Ni; Benjamin Eysenbach; Erfan Seyedsalehi; Michel Ma; Clement Gehring; Aditya Mahajan; Pierre-Luc Bacon (ICLR, 2024)

Do Transformer World Models Give Better Policy Gradients? - Michel Ma; Tianwei Ni; Clement Gehring; Pierluca D'Oro; Pierre-Luc Bacon (ICML, 2024)

Teaching Large Language Models to Reason through Learning and Forgetting. - Tianwei Ni; Allen Nie; Sapana Chaudhary; Yao Liu 009; Huzefa Rangwala; Rasool Fakoor (CoRR, 2025)

Understanding Behavioral Metric Learning: A Large-Scale Study on Distracting Reinforcement Learning Environments. - Ziyan Luo; Tianwei Ni; Pierre-Luc Bacon; Doina Precup; Xujie Si (CoRR, 2025)