| thunil/Physics-Based-Deep-Learning |
1,536 |
|
0 |
0 |
over 2 years ago |
0 |
|
1 |
|
|
| Links to works on deep learning algorithms for physics problems, TUM-I15 and beyond |
| SciML/NeuralPDE.jl |
864 |
|
0 |
0 |
over 2 years ago |
0 |
|
127 |
other |
Julia |
| Physics-Informed Neural Networks (PINN) Solvers of (Partial) Differential Equations for Scientific Machine Learning (SciML) accelerated simulation |
| jcmgray/quimb |
390 |
|
0 |
0 |
over 2 years ago |
0 |
|
52 |
other |
Python |
| A python library for quantum information and many-body calculations including tensor networks. |
| iml-wg/HEPML-LivingReview |
293 |
|
0 |
0 |
over 2 years ago |
0 |
|
14 |
|
TeX |
| Living Review of Machine Learning for Particle Physics |
| sciann/sciann |
267 |
|
0 |
0 |
over 2 years ago |
96 |
April 19, 2022 |
51 |
other |
Python |
| Deep learning for Engineers - Physics Informed Deep Learning |
| PML-UCF/pinn |
103 |
|
0 |
0 |
almost 4 years ago |
3 |
August 27, 2020 |
2 |
mit |
Python |
| Physics-informed neural networks package |
| pierremtb/PINNs-TF2.0 |
91 |
|
0 |
0 |
almost 5 years ago |
0 |
|
4 |
mit |
Mathematica |
| TensorFlow 2.0 implementation of Maziar Raissi's Physics Informed Neural Networks (PINNs). |
| higgsfield/interaction_network_pytorch |
79 |
|
0 |
0 |
over 8 years ago |
0 |
|
2 |
|
Jupyter Notebook |
| Pytorch Implementation of Interaction Networks for Learning about Objects, Relations and Physics |
| AmeyaJagtap/XPINNs |
66 |
|
0 |
0 |
over 3 years ago |
0 |
|
0 |
mit |
|
| Extended Physics-Informed Neural Networks (XPINNs): A Generalized Space-Time Domain Decomposition Based Deep Learning Framework for Nonlinear Partial Differential Equations |
| empyreanx/godot-snapshot-interpolation-demo |
53 |
|
0 |
0 |
about 11 years ago |
0 |
|
0 |
mit |
GDScript |
| A simple networked physics demo for the Godot engine using snapshot interpolation and UDP |
