csjiezhao / Physics-Based-Deep-LearningLinks
☆24Updated 3 years ago
Alternatives and similar repositories for Physics-Based-Deep-Learning
Users that are interested in Physics-Based-Deep-Learning are comparing it to the libraries listed below
Sorting:
- Physics Informed Deep Learning for Traffic State Estimation: Illustrations with LWR and CTM Models☆15Updated 2 years ago
- Discovering dynamic patterns from spatiotemporal data with time-varying low-rank autoregression. (IEEE TKDE'24)☆23Updated 6 months ago
- Differentiable Physics-informed Graph Networks☆67Updated 5 years ago
- Source code for "Deep Variational Koopman Models: Inferring Koopman Observations for Uncertainty-Aware Dynamics Modeling and Control" fro…☆40Updated 6 years ago
- A python implementation of Physics-informed Spline Learning for nonlinear dynamics discovery.☆26Updated 3 years ago
- ☆33Updated 6 months ago
- Consistent Koopman Autoencoders☆74Updated 2 years ago
- Physics-informed Dyna-style model-based deep reinforcement learning for dynamic control☆55Updated 3 years ago
- Official implementation of "Physics-Informed Long-Sequence Forecasting From Multi-Resolution Spatiotemporal Data".☆10Updated 2 years ago
- An official 're'-implementation of Physics-induced graph neural network: An application to wind-farm power estimation (PGNN).☆28Updated 3 years ago
- ☆36Updated 6 years ago
- Papers on Spatial-Temporal Graph Neural Networks☆26Updated 3 years ago
- Deep Learning - Predicting using Neural Ordinary Differential Equations - torchdiffeq.☆15Updated 4 years ago
- Deep identification of symbolic open-form PDEs via enhanced reinforcement-learning☆37Updated 6 months ago
- [AAAI24] LE-PDE-UQ endows deep learning-based surrogate models with robust and efficient uncertainty quantification capabilities for both…☆16Updated last year
- ☆13Updated 4 years ago
- Official PyTorch implementation of "Physics-aware Difference Graph Networks for Sparsely-Observed Dynamics" (https://openreview.net/forum…☆51Updated 5 years ago
- ☆30Updated 5 years ago
- Spatiotemporal graph convolutional network for wind speed prediction.☆38Updated 2 months ago
- Research project conducted at Pacific Northwest National Laboratory, exploring the use of physics-informed autoencoders to predict fluid …☆35Updated 2 years ago
- Physics Informed Neural Network for Time Series Forecasting☆12Updated 2 years ago
- Physics-incorporated Graph Neural Network Using Dynamic Higher-Order Spatio-temporal Graphs for Multivariate Time Series Imputation☆14Updated 11 months ago
- Pytorch implementation of Spatoi-temporal Differential Equation Network (STDEN).☆38Updated 2 years ago
- Theory-guided hard constraint projection (HCP): a knowledge-based data-driven scientific machine learning method☆61Updated 3 years ago
- ☆42Updated 3 years ago
- Official implementation for our paper "Unsupervised Learning of Lagrangian Dynamics from Images for Prediction and Control"☆19Updated 2 years ago
- 🌌 Applications of Physics-Informed ML: A collection of notebooks from my Masters research, exploring how machine learning can solve scie…☆11Updated 7 months ago
- Neural Networks with Physics-Informed Architectures and Constraints for Dynamical Systems Modeling☆48Updated 3 years ago
- PyTorch Implementation of Lusch et al DeepKoopman☆13Updated 2 years ago
- Generalizing to New Physical Systems via Context-Informed Dynamics Model☆25Updated last year