benmoseley / intro-to-jax-workshop
Introduction to JAX Workshop @ ETH Zurich, 25 June 2024
☆18Updated 2 months ago
Related projects: ⓘ
- ☆12Updated 2 months ago
- Discontinuity Computing Using Physics-Informed Neural Network☆19Updated 5 months ago
- Practicum on Supervised Learning in Function Spaces☆31Updated 2 years ago
- Neural network based solvers for partial differential equations and inverse problems . Implementation of physics-informed neural networks…☆16Updated 2 years ago
- Convolutional Solvers for Partial Differential Equations☆28Updated 4 years ago
- ☆47Updated last year
- Scientific Machine Learning Tutorials☆36Updated 2 years ago
- Using NVIDIA modulus for airfoil optimizations at different angles.☆23Updated last year
- XPINN code written in TensorFlow 2☆25Updated last year
- Derivative-Informed Neural Operator: An Efficient Framework for High-Dimensional Parametric Derivative Learning☆18Updated 8 months ago
- ☆45Updated last year
- TensorFlow 2.0 implementation of Yibo Yang, Paris Perdikaris’s adversarial Uncertainty Quantification in Physics Informed Neural Networks…☆17Updated last year
- Efficient and Scalable Physics-Informed Deep Learning and Scientific Machine Learning on top of Tensorflow for multi-worker distributed c…☆110Updated 2 years ago
- A python script to solve the Cahn-Hilliard equation using an implicit pseudospectral method☆31Updated 2 months ago
- ☆22Updated last year
- PDE Preserved Neural Network☆25Updated 2 months ago
- Stiff-PINN: Physics-Informed Neural Network for Stiff Chemical Kinetics☆48Updated 2 years ago
- Sparse Physics-based and Interpretable Neural Networks☆43Updated 2 years ago
- ☆82Updated 2 years ago
- A Python library for training neural ODEs.☆19Updated last month
- ETH Zürich AI in the Sciences and Engineering Master's course 2024☆19Updated last month
- ☆51Updated last week
- Example problems in Physics informed neural network in JAX☆69Updated last year
- A library for dimensionality reduction on spatial-temporal PDE☆58Updated 5 months ago
- GCA-ROM is a library which implements graph convolutional autoencoder architecture as a nonlinear model order reduction strategy.☆26Updated 2 months ago
- Multifidelity DeepONet☆25Updated last year
- Random snippets of code I've developed over the years (generally when bored)☆12Updated last year
- Reduced-Order Modeling of Fluid Flows with Transformers☆19Updated last year
- ☆31Updated this week
- This is the repository for the code used in the ICML23 paper called "Achieving High Accuracy with PINNs via Energy Natural Gradient Desce…☆10Updated last year