mia-jinns / jinns
Physics Informed Neural Networks (PINNs) + SPINNs + HyperPINNs with JAX π Check out our various notebooks to get started β οΈ Mirror repository of jinns (development happens on Gitlab)
β25Updated this week
Alternatives and similar repositories for jinns:
Users that are interested in jinns are comparing it to the libraries listed below
- To address some of the failure modes in training of physics informed neural networks, a Lagrangian architecture is designed to conform toβ¦β46Updated 2 years ago
- Codes associated with the manuscript titled "Multi-stage neural networks: Function approximator of machine precision"β38Updated 10 months ago
- Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Dataβ47Updated 4 years ago
- An interpretable data-driven framework for building generative reduced order models with embedded uncertainty quantificationβ31Updated last week
- Example problems in Physics informed neural network in JAXβ78Updated last year
- Bayesian optimized physics-informed neural network for parameter estimationβ24Updated 3 months ago
- Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEsβ25Updated 3 years ago
- when using, please cite "Bayesian Physics-Informed Neural Networks for real-world nonlinear dynamical systems", CMAME, https://doi.org/1β¦β63Updated 2 years ago
- β33Updated 2 months ago
- β167Updated last year
- β25Updated last year
- Practicum on Supervised Learning in Function Spacesβ32Updated 3 years ago
- A python implementation of Physics-informed Spline Learning for nonlinear dynamics discovery.β25Updated 3 years ago
- β30Updated last year
- This repository contains code, which was used to generate large-scale results in the HINTS paper.β26Updated 4 months ago
- Update PDEKoopman code to Tensorflow 2β23Updated 3 years ago
- Semi-supervised Invertible Neural Operators for Bayesian Inverse Problemsβ13Updated 9 months ago
- This repository contains the code and models for our paper "Investigating and Mitigating Failure Modes in Physics-informed Neural Networkβ¦β17Updated last year
- Implementing a physics-informed DeepONet from scratchβ34Updated last year
- Official repo for separable operator networks -- extreme-scale operator learning for parametric PDEs.β24Updated 4 months ago
- A library for dimensionality reduction on spatial-temporal PDEβ63Updated 10 months ago
- Differential equation neural operatorβ20Updated last year
- Sparse Physics-based and Interpretable Neural Networksβ47Updated 3 years ago
- β15Updated 6 months ago
- Physics Informed Fourier Neural Operatorβ18Updated 3 months ago
- β31Updated last year
- β14Updated 2 years ago
- Efficient and Scalable Physics-Informed Deep Learning and Scientific Machine Learning on top of Tensorflow for multi-worker distributed cβ¦β114Updated 3 years ago
- PINNs-JAX, Physics-informed Neural Networks (PINNs) implemented in JAX.β38Updated 5 months ago
- β22Updated 7 months ago