KindXiaoming / aipoincareLinks
Counting the number of conservation laws from trajectory data
☆21Updated 4 years ago
Alternatives and similar repositories for aipoincare
Users that are interested in aipoincare are comparing it to the libraries listed below
Sorting:
- Repo to the paper "Lie Point Symmetry Data Augmentation for Neural PDE Solvers"☆57Updated 2 years ago
- Code for the Paper "Physics-Informed Gaussian Process Regression Generalizes Linear PDE Solvers"☆33Updated last year
- This is project page for the paper "RG-Flow: a hierarchical and explainable flow model based on renormalization group and sparse prior". …☆88Updated 3 years ago
- ☆23Updated last year
- Code for the paper "Rational neural networks", NeurIPS 2020☆29Updated 4 years ago
- Solving High Dimensional Partial Differential Equations with Deep Neural Networks☆34Updated 4 years ago
- 18.336 - Fast Methods for Partial Differential and Integral Equations☆189Updated last year
- Reference implementation of Finite Element Networks as proposed in "Learning the Dynamics of Physical Systems from Sparse Observations wi…☆69Updated last year
- ☆42Updated 5 years ago
- DeepONets, (Fourier) Neural Operators, Physics-Informed Neural Operators, and more in Julia☆291Updated last year
- code for "Neural Conservation Laws A Divergence-Free Perspective".☆41Updated 3 years ago
- ☆74Updated 5 years ago
- Learning Green's functions of partial differential equations with deep learning.☆71Updated 2 years ago
- Forward-Backward Stochastic Neural Networks: Deep Learning of High-dimensional Partial Differential Equations☆156Updated 5 years ago
- Example code for paper: Automatic Differentiation to Simultaneously Identify Nonlinear Dynamics and Extract Noise Probability Distributio…☆61Updated 3 years ago
- Code for "Nonlinear stochastic modeling with Langevin regression" J. L. Callaham, J.-C. Loiseau, G. Rigas, and S. L. Brunton☆27Updated 3 years ago
- Python codes for Introduction to Computational Stochastic PDE☆49Updated last month
- ☆30Updated last month
- Refining continuous-in-depth neural networks☆42Updated 4 years ago
- Practicum on Supervised Learning in Function Spaces☆34Updated 3 years ago
- How to train a neural ODE for time series/weather forecasting☆39Updated 2 years ago
- Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"☆171Updated 3 years ago
- Datasets and code for results presented in the ProbConserv paper☆56Updated last year
- Neural Stochastic PDEs: resolution-invariant modelling of continuous spatiotemporal dynamics☆54Updated 3 years ago
- Code for the paper: Solving and Learning Nonlinear PDEs with Gaussian Processes☆40Updated 6 months ago
- Companion code for "Solving Nonlinear and High-Dimensional Partial Differential Equations via Deep Learning" by A. Al-Aradi, A. Correia, …☆122Updated 6 years ago
- Code to estimate Renormalized Mutual Information in simple settings☆13Updated 4 years ago
- A curated list of awesome Scientific Machine Learning (SciML) papers, resources and software☆77Updated 2 years ago
- ☆21Updated 3 years ago
- Efficient, Accurate, and Streamlined Training of Physics-Informed Neural Networks☆59Updated 10 months ago