Songming Liu

According to our database1, Songming Liu authored at least 10 papers between 2021 and 2024.

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Bibliography

2024
DPOT: Auto-Regressive Denoising Operator Transformer for Large-Scale PDE Pre-Training.
CoRR, 2024

Preconditioning for Physics-Informed Neural Networks.
CoRR, 2024

2023
PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs.
CoRR, 2023

Reward Informed Dreamer for Task Generalization in Reinforcement Learning.
CoRR, 2023

MultiAdam: Parameter-wise Scale-invariant Optimizer for Multiscale Training of Physics-informed Neural Networks.
Proceedings of the International Conference on Machine Learning, 2023

NUNO: A General Framework for Learning Parametric PDEs with Non-Uniform Data.
Proceedings of the International Conference on Machine Learning, 2023

GNOT: A General Neural Operator Transformer for Operator Learning.
Proceedings of the International Conference on Machine Learning, 2023

2022
Physics-Informed Machine Learning: A Survey on Problems, Methods and Applications.
CoRR, 2022

A Unified Hard-Constraint Framework for Solving Geometrically Complex PDEs.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021
Deep-reinforcement-learning-based images segmentation for quantitative analysis of gold immunochromatographic strip.
Neurocomputing, 2021


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