ASEM000 / Physics-informed-neural-network-in-JAXLinks
Example problems in Physics informed neural network in JAX
☆80Updated last year
Alternatives and similar repositories for Physics-informed-neural-network-in-JAX
Users that are interested in Physics-informed-neural-network-in-JAX are comparing it to the libraries listed below
Sorting:
- ☆97Updated 3 years ago
- Applications of PINOs☆126Updated 2 years ago
- Efficient and Scalable Physics-Informed Deep Learning and Scientific Machine Learning on top of Tensorflow for multi-worker distributed c…☆115Updated 3 years ago
- Sparse Physics-based and Interpretable Neural Networks☆50Updated 3 years ago
- ☆53Updated 2 years ago
- when using, please cite "Bayesian Physics-Informed Neural Networks for real-world nonlinear dynamical systems", CMAME, https://doi.org/1…☆70Updated 2 years ago
- ☆212Updated 3 years ago
- [Neurips 2024] A benchmark suite for autoregressive neural emulation of PDEs. (≥46 PDEs in 1D, 2D, 3D; Differentiable Physics; Unrolled T…☆75Updated last month
- ☆116Updated 5 years ago
- PINNs-JAX, Physics-informed Neural Networks (PINNs) implemented in JAX.☆48Updated 9 months ago
- ☆143Updated 2 years ago
- Codes associated with the manuscript titled "Multi-stage neural networks: Function approximator of machine precision"☆46Updated last year
- ☆62Updated 7 months ago
- An RL-Gym for Challenge Problems in Data-Driven Modeling and Control of Fluid Dynamics.☆75Updated this week
- Deep learning library for solving differential equations on top of PyTorch.☆61Updated 4 years ago
- ☆41Updated 5 years ago
- This is the repository for the code used in the ICML23 paper called "Achieving High Accuracy with PINNs via Energy Natural Gradient Desce…☆20Updated 8 months ago
- We propose a conservative physics-informed neural network (cPINN) on decompose domains for nonlinear conservation laws. The conservation …☆71Updated 2 years ago
- Code for the paper "Poseidon: Efficient Foundation Models for PDEs"☆144Updated 2 months ago
- ☆166Updated last year
- Physics-constrained auto-regressive convolutional neural networks for dynamical PDEs☆92Updated 3 years ago
- Multifidelity DeepONet☆33Updated last year
- Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs☆31Updated 3 years ago
- Extended Physics-Informed Neural Networks (XPINNs): A Generalized Space-Time Domain Decomposition Based Deep Learning Framework for Nonli…☆197Updated 2 years ago
- ☆109Updated 4 months ago
- Implementation of PINNs in TensorFlow 2☆78Updated last year
- ☆26Updated 11 months ago
- hPINN: Physics-informed neural networks with hard constraints☆134Updated 3 years ago
- Physics Informed Neural Network (PINN) for Burgers' equation.☆70Updated 10 months ago
- Neural network based solvers for partial differential equations and inverse problems . Implementation of physics-informed neural networks…☆151Updated 5 months ago