Liu Yang
University of California, Los Angeles(US)Chengdu University of Technology(CN)
Publications by Year
Research Areas
Model Reduction and Neural Networks, Probabilistic and Robust Engineering Design, Gaussian Processes and Bayesian Inference, Generative Adversarial Networks and Image Synthesis, Topic Modeling
Most-Cited Works
- → Physics-informed machine learning(2021)5,785 cited
- → B-PINNs: Bayesian physics-informed neural networks for forward and inverse PDE problems with noisy data(2020)983 cited
- → Physics-Informed Generative Adversarial Networks for Stochastic Differential Equations(2020)404 cited
- → Reinforcement learning for bluff body active flow control in experiments and simulations(2020)238 cited
- → Long Range Arena: A Benchmark for Efficient Transformers(2020)195 cited
- → Solving Inverse Stochastic Problems from Discrete Particle Observations Using the Fokker--Planck Equation and Physics-Informed Neural Networks(2021)112 cited
- → Neural-net-induced Gaussian process regression for function approximation and PDE solution(2019)76 cited
- → Learning functional priors and posteriors from data and physics(2022)55 cited
- → In-context operator learning with data prompts for differential equation problems(2023)39 cited