TaikiMiyagawa / FunctionalPINN
This is the official implementation of physics-informed neural networks for functional differential equations (Functional PINN) proposed in ["Physics-informed Neural Networks for Functional Differential Equations: Cylindrical Approximation and Its Convergence Guarantees", NeurIPS 2024].
☆11Updated last week
Alternatives and similar repositories for FunctionalPINN:
Users that are interested in FunctionalPINN are comparing it to the libraries listed below
- AL4PDE: A Benchmark for Active Learning for Neural PDE Solvers☆21Updated last month
- ☆14Updated 3 years ago
- Tackling the Curse of Dimensionality with Physics-Informed Neural Networks☆12Updated 11 months ago
- Differential equation neural operator☆20Updated last year
- ☆17Updated last year
- Training neural networks to disentangle conservative and dissipative dynamics☆10Updated 3 years ago
- ☆16Updated 8 months ago
- Domain Agnostic Fourier Neural Operators (DAFNO)☆14Updated 7 months ago
- PROSE: Predicting Multiple Operators and Symbolic Expressions☆23Updated 2 weeks ago
- ☆12Updated last year
- ☆16Updated last year
- [ICLR24] A boundary-embedded neural operator that incorporates complex boundary shape and inhomogeneous boundary values☆26Updated 4 months ago
- Symbolic physics learner: Discovering governing equations via Monte Carlo tree search☆23Updated last year
- Code for orthogonal neural operator☆15Updated last year
- Official codebase for "Score-based Diffusion Models in Function Space"☆10Updated 2 months ago
- Bayesian optimization with Standard Gaussian Processes on high dimensional benchmarks☆11Updated this week
- ☆11Updated 3 years ago
- Code and data for paper named: Large language models for automatic equation discovery of nonlinear dynamics☆10Updated last month
- Neural Stochastic PDEs: resolution-invariant modelling of continuous spatiotemporal dynamics☆51Updated 2 years ago
- ☆11Updated 2 years ago
- ☆10Updated 4 years ago
- Code for the paper: Solving and Learning Nonlinear PDEs with Gaussian Processes☆39Updated 5 months ago
- ☆16Updated last month
- [ICLR 2024] Scaling physics-informed hard constraints with mixture-of-experts.☆32Updated 9 months ago
- Solving High Frequency and Multi-Scale PDEs with Gaussian Processes (ICLR 2024)☆19Updated 10 months ago
- A tool for generating PDEs ground truth datasets from ARCSim, FEniCS and SU2☆37Updated 3 years ago
- PyTorch implemention of the Position-induced Transformer for operator learning in partial differential equations☆17Updated 5 months ago
- ☆7Updated 4 months ago
- [ICML 2024] Official Pytorch implementation of the paper "A Neural-Guided Dynamic Symbolic Network for Exploring Mathematical Expressions…☆17Updated 3 months ago
- Synthetic data library used in operator learning for PDE problems that overcomes dependence on classical solvers such as finite differenc…☆13Updated 8 months ago