Deep-reinforcement-learning-based images segmentation for quantitative analysis of gold immunochromatographic strip. - Nianyin Zeng; Han Li 004; Zidong Wang 001; Weibo Liu 001; Songming Liu; Fuad E. Alsaadi; Xiaohui Liu 001 (Neurocomputing, 2021)

A Unified Hard-Constraint Framework for Solving Geometrically Complex PDEs. - Songming Liu; Zhongkai Hao; Chengyang Ying; Hang Su 006; Jun Zhu 001; Ze Cheng (NeurIPS, 2022)

Physics-Informed Machine Learning: A Survey on Problems, Methods and Applications. - Zhongkai Hao; Songming Liu; Yichi Zhang; Chengyang Ying; Yao Feng 002; Hang Su 006; Jun Zhu 001 (CoRR, 2022)

Vessel Traffic Flow Prediction and Analysis Based on Ship Big Data. - Tong Wang; Xiaoyang Gai; Songming Liu; Shan Gao; Min Ouyang; Liwei Chen (ChineseCSCW (1), 2023)

Arterial Traffic Optimization Algorithm Based on Deep Reinforcement Learning and Green Wave Coordination Control in Complex Lane Queuing Conditions. - Tong Wang; Songming Liu; Liwei Chen; Min Ouyang; Shan Gao; Yingxue Zhang (ChineseCSCW (2), 2023)

GNOT: A General Neural Operator Transformer for Operator Learning. - Zhongkai Hao; Zhengyi Wang; Hang Su 006; Chengyang Ying; Yinpeng Dong; Songming Liu; Ze Cheng; Jian Song; Jun Zhu 001 (ICML, 2023)

NUNO: A General Framework for Learning Parametric PDEs with Non-Uniform Data. - Songming Liu; Zhongkai Hao; Chengyang Ying; Hang Su 006; Ze Cheng; Jun Zhu 001 (ICML, 2023)

MultiAdam: Parameter-wise Scale-invariant Optimizer for Multiscale Training of Physics-informed Neural Networks. - Jiachen Yao; Chang Su; Zhongkai Hao; Songming Liu; Hang Su 006; Jun Zhu 001 (ICML, 2023)

Reward Informed Dreamer for Task Generalization in Reinforcement Learning. - Chengyang Ying; Zhongkai Hao; Xinning Zhou; Hang Su 006; Songming Liu; Jialian Li; Dong Yan; Jun Zhu 001 (CoRR, 2023)

Reference Neural Operators: Learning the Smooth Dependence of Solutions of PDEs on Geometric Deformations. - Ze Cheng; Zhongkai Hao; Xiaoqiang Wang; Jianing Huang; Youjia Wu; Xudan Liu; Yiru Zhao; Songming Liu; Hang Su 006 (ICML, 2024)

DPOT: Auto-Regressive Denoising Operator Transformer for Large-Scale PDE Pre-Training. - Zhongkai Hao; Chang Su; Songming Liu; Julius Berner; Chengyang Ying; Hang Su 006; Anima Anandkumar; Jian Song; Jun Zhu 001 (ICML, 2024)

Fourier Controller Networks for Real-Time Decision-Making in Embodied Learning. - Hengkai Tan; Songming Liu; Kai Ma; Chengyang Ying; Xingxing Zhang 001; Hang Su 006; Jun Zhu 001 (ICML, 2024)

PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs. - Zhongkai Hao; Jiachen Yao; Chang Su; Hang Su 006; Ziao Wang; Fanzhi Lu; Zeyu Xia 003; Yichi Zhang; Songming Liu; Lu Lu; Jun Zhu 001 (NeurIPS, 2024)

Preconditioning for Physics-Informed Neural Networks. - Songming Liu; Chang Su; Jiachen Yao; Zhongkai Hao; Hang Su 006; Youjia Wu; Jun Zhu 001 (CoRR, 2024)

ManiBox: Enhancing Spatial Grasping Generalization via Scalable Simulation Data Generation. - Hengkai Tan; Xuezhou Xu; Chengyang Ying; Xinyi Mao; Songming Liu; Xingxing Zhang 001; Hang Su 006; Jun Zhu 001 (CoRR, 2024)

RDT-1B: a Diffusion Foundation Model for Bimanual Manipulation. - Songming Liu; Lingxuan Wu; Bangguo Li; Hengkai Tan; Huayu Chen; Zhengyi Wang; Ke Xu; Hang Su 006; Jun Zhu 001 (ICLR, 2025)

Regulating learning module for patient monitoring interactive event detecting robots. - Fan Wu; Lin Wu; Songming Liu; Ghulam Abbas 003; Salwa Othmen; Jingming Wang (Expert Syst. Appl., 2025)