erisahasani / synthetic-data-for-neural-operatorsLinks
Synthetic data library used in operator learning for PDE problems that overcomes dependence on classical solvers such as finite differences, finite element, etc.
☆15Updated last year
Alternatives and similar repositories for synthetic-data-for-neural-operators
Users that are interested in synthetic-data-for-neural-operators are comparing it to the libraries listed below
Sorting:
- ☆22Updated 3 months ago
- Spectral Neural Operator☆78Updated last year
- Source code of "Learning nonlinear operators in latent spaces for real-time predictions of complex dynamics in physical systems."☆69Updated 4 months ago
- Differential equation neural operator☆23Updated 2 years ago
- ☆46Updated 6 months ago
- AL4PDE: A Benchmark for Active Learning for Neural PDE Solvers☆27Updated 3 months ago
- Practicum on Supervised Learning in Function Spaces☆33Updated 3 years ago
- PROSE: Predicting Multiple Operators and Symbolic Expressions☆28Updated 5 months ago
- Learning with Higher Expressive Power than Neural Networks (On Learning PDEs)☆16Updated 4 years ago
- Official repo for separable operator networks -- extreme-scale operator learning for parametric PDEs.☆29Updated 10 months ago
- An unofficial implementation of the Fourier Neural Operator in Flax☆18Updated last year
- ☆83Updated last year
- SymDer: Symbolic Derivative Approach to Discovering Sparse Interpretable Dynamics from Partial Observations☆21Updated 3 years ago
- Neural Stochastic PDEs: resolution-invariant modelling of continuous spatiotemporal dynamics☆53Updated 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 3 months ago
- ☆36Updated 2 years ago
- PDE Preserved Neural Network☆55Updated 4 months ago
- Benchmarking of diffusion models for global field reconstruction from sparse observations☆25Updated 9 months ago
- ☆16Updated last year
- Multiwavelets-based operator model☆64Updated 3 years ago
- Code for Characterizing Scaling and Transfer Learning Behavior of FNO in SciML☆46Updated 2 years ago
- ☆59Updated 3 weeks ago
- A python implementation of Physics-informed Spline Learning for nonlinear dynamics discovery.☆27Updated 3 years ago
- Official PyTorch implementation of the Vectorized Conditional Neural Field.☆15Updated last year
- ETH Zürich AI in the Sciences and Engineering Master's course 2024☆39Updated last year
- ☆42Updated 2 years ago
- Code for the paper "Poseidon: Efficient Foundation Models for PDEs"☆152Updated 5 months ago
- Benchmarking Autoregressive Conditional Diffusion Models for Turbulent Flow Simulation☆96Updated 9 months ago
- ☆11Updated 9 months ago
- ☆36Updated last week