mia-jinns / jinnsLinks
Physics Informed Neural Networks (PINNs) + SPINNs + HyperPINNs + Adaptative Loss Weights with JAX π Check out our various notebooks to get started β οΈ Mirror repository of jinns (development happens on Gitlab)
β33Updated this week
Alternatives and similar repositories for jinns
Users that are interested in jinns are comparing it to the libraries listed below
Sorting:
- Source code of "Learning nonlinear operators in latent spaces for real-time predictions of complex dynamics in physical systems."β63Updated 2 months ago
- Official repo for separable operator networks -- extreme-scale operator learning for parametric PDEs.β27Updated 8 months ago
- Introduction to JAX Workshop @ ETH Zurich, 25 June 2024β36Updated 3 months ago
- β35Updated 3 weeks ago
- Pseudospectral Kolmogorov Flow Solverβ40Updated last year
- β29Updated 2 years ago
- β38Updated last year
- To address some of the failure modes in training of physics informed neural networks, a Lagrangian architecture is designed to conform toβ¦β49Updated 2 years ago
- A library for dimensionality reduction on spatial-temporal PDEβ66Updated last year
- Generative Learning for Forecasting the Dynamics of High Dimensional Complex Systemsβ34Updated 4 months ago
- XPINN code written in TensorFlow 2β28Updated 2 years ago
- This repository contains code, which was used to generate large-scale results in the HINTS paper.β29Updated 9 months ago
- Competitive Physics Informed Networksβ30Updated 9 months ago
- β17Updated 6 months ago
- Simple demo on implementing data driven and physics informed Deep O Nets in pytorchβ11Updated last year
- Codes associated with the manuscript titled "Multi-stage neural networks: Function approximator of machine precision"β46Updated last year
- Derivative-Informed Neural Operator: An Efficient Framework for High-Dimensional Parametric Derivative Learningβ16Updated last year
- β20Updated last month
- Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Dataβ49Updated 4 years ago
- Example problems in Physics informed neural network in JAXβ80Updated last year
- Original implementation of fast PINN optimization with RBA weightsβ57Updated 3 months ago
- β26Updated last year
- Multifidelity DeepONetβ34Updated 2 years ago
- Sparse Physics-based and Interpretable Neural Networksβ51Updated 3 years ago
- FastVPINNs - A tensor-driven acceleration of VPINNs for complex geometriesβ42Updated 5 months ago
- The unsupervised learning problem trains a diffeomorphic spatio-temporal grid, that registers the output sequence of the PDEs onto a non-β¦β19Updated 2 years ago
- Python codes for Locally Adaptive Activation Function (LAAF) used in deep neural networks. Please cite this work as "A D Jagtap, K Kawaβ¦β40Updated 2 years ago
- Semi-supervised Invertible Neural Operators for Bayesian Inverse Problemsβ13Updated last year
- β32Updated last year
- A python implementation of Physics-informed Spline Learning for nonlinear dynamics discovery.β26Updated 3 years ago