PyShred-Dev / PySHREDLinks
PySHRED: Package for Shallow Recurrent Decoding
☆27Updated 7 months ago
Alternatives and similar repositories for PySHRED
Users that are interested in PySHRED are comparing it to the libraries listed below
Sorting:
- Discovers high dimensional models from 1D data using deep delay autoencoders☆38Updated 2 years ago
- Code for paper Sparse identification of nonlinear dynamics with Shallow Recurrent Decoder Networks.☆35Updated last week
- ☆200Updated 10 months ago
- Code for the paper "Poseidon: Efficient Foundation Models for PDEs"☆168Updated 9 months ago
- This repository is the official implementation of the paper Convolutional Neural Operators for robust and accurate learning of PDEs☆205Updated 2 months ago
- Implementation of Fourier Neural Operator using PyTorch☆29Updated 3 months ago
- Code and files related to random side projects☆21Updated 4 years ago
- [Neurips 2024] A benchmark suite for autoregressive neural emulation of PDEs. (≥46 PDEs in 1D, 2D, 3D; Differentiable Physics; Unrolled T…☆97Updated 2 months ago
- Welcome to the CTF for Science Framework, a modular and extensible platform designed for benchmarking modeling methods on dynamic systems…☆36Updated last week
- mathLab mirror of Python Dynamic Mode Decomposition☆113Updated 11 months ago
- A library for dimensionality reduction on spatial-temporal PDE☆71Updated last month
- ☆241Updated 4 years ago
- ☆288Updated last year
- Source code of "Learning nonlinear operators in latent spaces for real-time predictions of complex dynamics in physical systems."☆76Updated 9 months ago
- This repository is the official project page of the course AI in the Sciences and Engineering, ETH Zurich.☆330Updated 8 months ago
- An interpretable data-driven framework for building generative reduced order models with embedded uncertainty quantification☆47Updated 2 weeks ago
- Pseudospectral Kolmogorov Flow Solver☆42Updated 2 years ago
- A library for Koopman Neural Operator with Pytorch.☆317Updated last year
- ☆379Updated 4 years ago
- Benchmarking Autoregressive Conditional Diffusion Models for Turbulent Flow Simulation☆106Updated last year
- ☆402Updated 2 months ago
- Characterizing possible failure modes in physics-informed neural networks.☆150Updated 4 years ago
- ☆274Updated 3 years ago
- [ICLR 2025] Neural Operator-Assisted Computational Fluid Dynamics in PyTorch☆72Updated 2 months ago
- ☆12Updated last year
- ☆50Updated 2 years ago
- ☆41Updated 2 years ago
- ☆41Updated 5 months ago
- Spectral Neural Operator☆79Updated 2 years ago
- ☆110Updated 4 years ago