FICAL: Focal Inter-Class Angular Loss for Image Classification. - Xinran Wei; Dongliang Chang; Jiyang Xie 001; Yixiao Zheng; Chen Gong 002; Chuang Zhang; Zhanyu Ma (VCIP, 2019)

Cooperative Policy Learning with Pre-trained Heterogeneous Observation Representations. - Wenlei Shi; Xinran Wei; Jia Zhang 004; Xiaoyuan Ni; Arthur Jiang; Jiang Bian 002; Tie-Yan Liu (AAMAS, 2021)

LordNet: Learning to Solve Parametric Partial Differential Equations without Simulated Data. - Wenlei Shi; Xinquan Huang; Xiaotian Gao; Xinran Wei; Jia Zhang 004; Jiang Bian 002; Mao Yang 004; Tie-Yan Liu (CoRR, 2022)

AI Agent as Urban Planner: Steering Stakeholder Dynamics in Urban Planning via Consensus-based Multi-Agent Reinforcement Learning. - Kejiang Qian; Lingjun Mao; Xin Liang; Yimin Ding; Jin Gao; Xinran Wei; Ziyi Guo; Jiajie Li (CoRR, 2023)

Plasmonic Resonance Coupling of Nanodisk Array/Thin Film on the Optical Fiber Tip for Integrated and Miniaturized Sensing Detection. - Hao He; Xinran Wei; Yijin He; Yuzhang Liang; Yurui Fang; Wei Peng (Sensors, 2023)

Long-Short-Range Message-Passing: A Physics-Informed Framework to Capture Non-Local Interaction for Scalable Molecular Dynamics Simulation. - Yunyang Li; Yusong Wang; Lin Huang; Han Yang; Xinran Wei; Jia Zhang 004; Tong Wang 014; Zun Wang; Bin Shao; Tie-Yan Liu (ICLR, 2024)

Self-Consistency Training for Density-Functional-Theory Hamiltonian Prediction. - He Zhang; Chang Liu 030; Zun Wang; Xinran Wei; Siyuan Liu 005; Nanning Zheng 001; Bin Shao; Tie-Yan Liu (ICML, 2024)

Infusing Self-Consistency into Density Functional Theory Hamiltonian Prediction via Deep Equilibrium Models. - Zun Wang; Chang Liu 030; Nianlong Zou; He Zhang; Xinran Wei; Lin Huang; Lijun Wu 003; Bin Shao (NeurIPS, 2024)

Self-Consistency Training for Hamiltonian Prediction. - He Zhang; Chang Liu 030; Zun Wang; Xinran Wei; Siyuan Liu 005; Nanning Zheng 001; Bin Shao; Tie-Yan Liu (CoRR, 2024)

LordNet: An efficient neural network for learning to solve parametric partial differential equations without simulated data. - Xinquan Huang; Wenlei Shi; Xiaotian Gao; Xinran Wei; Jia Zhang 004; Jiang Bian 002; Mao Yang 004; Tie-Yan Liu (Neural Networks, 2024)

Enhancing the Scalability and Applicability of Kohn-Sham Hamiltonians for Molecular Systems. - Yunyang Li; Zaishuo Xia; Lin Huang; Xinran Wei; Samuel Harshe; Han Yang; Erpai Luo; Zun Wang; Jia Zhang 004; Chang Liu 030; Bin Shao; Mark Gerstein (ICLR, 2025)

E2Former: A Linear-time Efficient and Equivariant Transformer for Scalable Molecular Modeling. - Yunyang Li; Lin Huang; Zhihao Ding; Chu Wang; Xinran Wei; Han Yang; Zun Wang; Chang Liu 030; Yu Shi; Peiran Jin; Jia Zhang 004; Mark Gerstein; et al. (CoRR, 2025)

Efficient and Scalable Density Functional Theory Hamiltonian Prediction through Adaptive Sparsity. - Erpai Luo; Xinran Wei; Lin Huang; Yunyang Li; Han Yang; Zun Wang; Chang Liu; Zaishuo Xia; Jia Zhang; Bin Shao (CoRR, 2025)

Enhancing the Scalability and Applicability of Kohn-Sham Hamiltonians for Molecular Systems. - Yunyang Li; Zaishuo Xia; Lin Huang; Xinran Wei; Han Yang; Sam Harshe; Zun Wang; Chang Liu 030; Jia Zhang 004; Bin Shao; Mark B. Gerstein (CoRR, 2025)

Accurate and scalable exchange-correlation with deep learning. - Giulia Luise; Chin-Wei Huang; Thijs Vogels; Derk P. Kooi; Sebastian Ehlert; Stephanie Lanius; Klaas J. H. Giesbertz; Amir Karton; Deniz Gunceler; Megan Stanley; Wessel P. Bruinsma; Lin Huang; et al. (CoRR, 2025)