S Liang and H Yang, Finite expression method for solving high-dimensional partial differential equations, Journal of Machine Learning Research, Accepted and In Production (2025)

G Hardwick, S Liang and H Yang, Solving High-Dimensional Partial Integral Differential Equations: The Finite Expression Method, Journal of Computational Physics 114273 (2025) 

J Du (Undergrad student), S Liang and C Wang, Learning Epidemiological Dynamics via the Finite Expression Method, Journal of Machine Learning for Modeling and Computing (2025)

S Liang, L Zhu, C Yang and X Li, Artificial-Intelligence-Driven Shot Reduction in Quantum Measurement, Chemical Physics Reviews, Volume 5, 041403 (2024)

S Liang, AN Singh, Y Zhu, DT Limmer and C Yang, Probing Reaction Channels via Reinforcement Learning, Machine Learning: Science and Technology 4 (4) (2023)

S Liang, K Kowalski, C Yang, NP Bauman, Exploring the Nexus of Many-Body Theories through Neural Network Techniques: the Tangent Model, Machine Learning: Science and Technology 6, 025040 (2025)

S Liang, K Kowalski, C Yang and NP Bauman, Effective Many-body Interactions in Reduced-Dimensionality Spaces through NNs, Physical Review Research 6, 043287 (2024)

Z Huang, S Liang, M Liang, A Generic Shared Attention Mechanism for Various Backbone Neural Networks, Neurocomputing, Volume 611, 128697 (2024)

S Liang, L Lyu, C Wang and H Yang, Reproducing Activation Function for Deep Learning, Communications in Mathematical Sciences, 22 (2), 285 – 314 (2024)

Z Huang, S Liang, H Yang, L Lin, On Fast Simulation of Dynamical System with Neural Vector Enhanced Numerical Solver, Scientific reports 13 (1), 15254 (2023)

J Xue, N Jiang, S Liang, Q Pang, T Yabe, SV Ukkusuri and J Ma, Quantifying Spatial Homogeneity of Urban Road Networks via Graph Neural Networks, Nature Machine Intelligence 4 (cover paper) (2022)

Z Huang, S Liang, M Liang, A Generic Shared Attention Mechanism for Various Backbone Neural Networks, Neurocomputing, Volume 611, 128697 (2024)

S Liang, SW Jiang, J Harlim and H Yang, Solving PDEs on Unknown Manifolds with Machine Learning, Applied and Computational Harmonic Analysis, Volume 71, 101652 (2024)

S Liang, L Lyu, C Wang and H Yang, Reproducing Activation Function for Deep Learning, Communications in Mathematical Sciences, 22 (2), 285 – 314 (2024)

H Bassi, Y Zhu, S Liang, J Yin, CC Reeves, V Vlcek and C Yang, Learning Nonlinear Integral Operators via Recurrent Neural Networks and Its Application, Machine Learning with Applications 15, 100524 (2024)

Y Gu, J Harlim, H Yang and S Liang, Stationary Density Estimation of Ito Diffusions Using Deep Learning, SIAM Journal on Numerical Analysis 61 (1), 45-82 (2023)

J Harlim, SW Jiang, S Liang and H Yang, Machine Learning for Prediction with Missing Dynamics, Journal of Computational Physics 428, 109922 (2021)

S Liang, Y Khoo and H Yang, Drop-Activation: Implicit Parameter Reduction and Harmonic Regularization, Communications on Applied Mathematics and Computation 3, 293-311 (2020)

Z Huang, M Liang, S Liang and S Zhong, Flat Local Minima for Continual Learning on Semantic Segmentation, International Conference on Multimedia Modeling 2025 (Best paper finalist)

Z Huang, S Liang, M Liang, W He, H Yang and L Lin, Lottery Ticket Hypothesis for Attention Mechanism in Residual Convolutional Neural Network, IEEE International Conference on Multimedia & Expo 2024

S Liang, Z Huang and H Zhang, Stiffness-aware Neural Network for Learning Hamiltonian Systems, International Conference on Learning Representations 2022

W He, Z Huang, M Liang, S Liang and H Yang, Blending Pruning Criteria for Convolutional Neural Networks, International Conference on Artificial Neural Networks 2021

Z Huang, S Liang, M Liang and H Yang, DIANet: Dense-and-Implicit Attention Network, Proceedings of the AAAI Conference on Artificial Intelligence 2020

S Liang, Z Huang, M Liang and H Yang, Instance Enhancement Batch Normalization: An Adaptive Regulator for Batch Noise, Proceedings of the AAAI Conference on Artificial Intelligence 2020