Bostanabad-Research-Group / GP-for-pde-solvingLinks
☆18Updated last year
Alternatives and similar repositories for GP-for-pde-solving
Users that are interested in GP-for-pde-solving are comparing it to the libraries listed below
Sorting:
- TorchFSM: Fourier Spectral Method with PyTorch☆53Updated last week
- ☆35Updated 2 years ago
- Code to accompany the paper "Discovery of Physics from Data: Universal Laws and Discrepancies"☆28Updated 5 years ago
- ☆41Updated 2 years ago
- [ICLR 2024] Scaling physics-informed hard constraints with mixture-of-experts.☆37Updated last year
- Code for "Nonlinear stochastic modeling with Langevin regression" J. L. Callaham, J.-C. Loiseau, G. Rigas, and S. L. Brunton☆26Updated 3 years ago
- The code enables to perform Bayesian inference in an efficient manner through the use of Hamiltonian Neural Networks (HNNs), Deep Neural …☆16Updated 2 years ago
- Bayesian optimization with Standard Gaussian Processes on high dimensional benchmarks☆18Updated 6 months ago
- A paper describing the implementation of PySR and SymbolicRegression.jl☆65Updated last year
- ☆104Updated 9 months ago
- Python Library for Generalized Gaussian Process Modeling☆27Updated 9 months ago
- A computational framework for finding symbolic expressions from physical datasets.☆61Updated 2 years ago
- Repo to the paper "Lie Point Symmetry Data Augmentation for Neural PDE Solvers"☆56Updated 2 years ago
- Datasets and code for results presented in the ProbConserv paper☆56Updated last year
- Intuitive scientific computing with dimension types for Jax, PyTorch, TensorFlow & NumPy☆94Updated last week
- Solving Inverse Physics Problems with Score Matching☆31Updated 2 years ago
- ☆10Updated 2 years ago
- AI Hilbert is an algebraic geometric based discovery system (based on Putinar's Positivstellensatz), that enables the discovery of fundam…☆41Updated 3 months ago
- This repository contains code for the paper "MAgNet: Mesh-Agnostic Neural PDE Solver" https://arxiv.org/abs/2210.05495☆38Updated 2 years ago
- Convolutional Differential Operators for Physics-based Deep Learning Study☆25Updated last year
- Benchmark for learning stiff problems using physics-informed machine learning☆12Updated 4 years ago
- Source code of: "Manifold learning-based polynomial chaos expansions for high-dimensional surrogate models".☆38Updated 3 years ago
- PyTorch implementation of the EQL network, a neural network for symbolic regression☆42Updated 4 years ago
- ☆25Updated 2 years ago
- Code for Lie Symmetries SSL paper☆24Updated last year
- ☆16Updated last year
- Code for the paper Universal Physics Transformers☆148Updated 6 months ago
- Learning Green's functions of partial differential equations with deep learning.☆71Updated 2 years ago
- Rethinking materials simulations: Blending DNS with Neural Operators☆21Updated last year
- Bayesian optimized physics-informed neural network for parameter estimation☆33Updated last year