benmoseley / symbolic-regression-with-deep-neural-networks-workshopLinks
Introductory workshop on using deep neural networks for symbolic regression
☆12Updated 5 months ago
Alternatives and similar repositories for symbolic-regression-with-deep-neural-networks-workshop
Users that are interested in symbolic-regression-with-deep-neural-networks-workshop are comparing it to the libraries listed below
Sorting:
- Introduction to JAX Workshop @ ETH Zurich, 25 June 2024☆37Updated 6 months ago
- Bayesian autoencoders for data-driven discovery of coordinates, governing equations and fundamental constants. Proceedings of the Royal S…☆10Updated last year
- Physics-informed neural networks☆16Updated 4 years ago
- Stochastic Physics-Informed Neural Networks: A Moment-Matching Framework for Learning Hidden Physics within Stochastic Differential Equat…☆14Updated 3 years ago
- Learning with Higher Expressive Power than Neural Networks (On Learning PDEs)☆16Updated 4 years ago
- Simple demo on implementing data driven and physics informed Deep O Nets in pytorch☆19Updated last year
- Synthetic Lagrangian Turbulence by Generative Diffusion Models☆26Updated 11 months ago
- PINNs-JAX, Physics-informed Neural Networks (PINNs) implemented in JAX.☆54Updated last year
- A repo to learn and curate PINN☆25Updated last year
- ☆34Updated last year
- CTF workshop deep learning tutorial and hackathon☆13Updated 2 years ago
- An interpretable data-driven framework for building generative reduced order models with embedded uncertainty quantification☆35Updated 7 months ago
- This repository contains code, which was used to generate large-scale results in the HINTS paper.☆32Updated last year
- Example code for paper: Automatic Differentiation to Simultaneously Identify Nonlinear Dynamics and Extract Noise Probability Distributio…☆59Updated 3 years ago
- Neural Galerkin☆16Updated 2 years ago
- [Neurips 2024] A benchmark suite for autoregressive neural emulation of PDEs. (≥46 PDEs in 1D, 2D, 3D; Differentiable Physics; Unrolled T…☆82Updated 5 months ago
- Source code for paper "Learning the Solution Operator of Boundary Value Problems using Graph Neural Networks"☆20Updated last year
- ☆12Updated 2 years ago
- Official Code for ICML 2024 paper "TENG: Time-Evolving Natural Gradient for Solving PDEs With Deep Neural Nets Toward Machine Precision"☆12Updated 11 months ago
- The code is associated with the paper entitled "KAN-ODEs: Kolmogorov-Arnold Network Ordinary Differential Equations for Learning Dynamica…☆33Updated 3 months ago
- TorchFSM: Fourier Spectral Method with PyTorch☆50Updated last week
- ☆17Updated 10 months ago
- Code for Mesh Transformer describes in the EAGLE dataset☆42Updated 8 months ago
- Code for paper Sparse identification of nonlinear dynamics with Shallow Recurrent Decoder Networks.☆32Updated last month
- This is the repository for the code used in the ICML23 paper called "Achieving High Accuracy with PINNs via Energy Natural Gradient Desce…☆22Updated last year
- ☆16Updated last year
- [ICLR 2024] Neural Spectral Methods: Self-supervised learning in the spectral domain.☆47Updated last year
- The public repository about our joint FINN research project☆38Updated 3 years ago
- AL4PDE: A Benchmark for Active Learning for Neural PDE Solvers☆29Updated 4 months ago
- Physics Informed Neural Networks (PINNs) + SPINNs + HyperPINNs + Adaptative Loss Weights with JAX 📓 Check out our various notebooks to g…☆39Updated last week