Time- and space-continuous neural PDE forecaster based on INRs and ODEs - ICLR 2023
☆75Jan 13, 2024Updated 2 years ago
Alternatives and similar repositories for DINo
Users that are interested in DINo are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- Generalizing to New Physical Systems via Context-Informed Dynamics Model☆28May 6, 2024Updated 2 years ago
- Repo to the paper "Message Passing Neural PDE Solvers"☆150Sep 11, 2024Updated last year
- ☆42Jul 22, 2024Updated 2 years ago
- ☆95Jul 18, 2023Updated 3 years ago
- Learning Dynamical Systems that Generalize Across Environments☆20Feb 10, 2022Updated 4 years ago
- End-to-end encrypted email - Proton Mail • AdSpecial offer: 40% Off Yearly / 80% Off First Month. All Proton services are open source and independently audited for security.
- About Code Release for "Solving High-Dimensional PDEs with Latent Spectral Models" (ICML 2023), https://arxiv.org/abs/2301.12664☆85Apr 10, 2025Updated last year
- PyTorch implemention of the Position-induced Transformer for operator learning in partial differential equations☆26Jun 3, 2025Updated last year
- Spectral Neural Operator☆83Dec 20, 2023Updated 2 years ago
- Code for "DPOT: Auto-Regressive Denoising Operator Transformer for Large-Scale PDE Pre-Training"☆60Jun 10, 2024Updated 2 years ago
- Code for Mesh Transformer describes in the EAGLE dataset☆43Feb 21, 2025Updated last year
- ☆311Sep 14, 2024Updated last year
- Official implementation of Scalable Transformer for PDE surrogate modelling☆57Mar 23, 2024Updated 2 years ago
- Code for reproducing the experiments in the paper "On Conditional Diffusion Models for PDE Simulations".☆28Nov 6, 2024Updated last year
- ☆97Sep 2, 2024Updated 2 years ago
- End-to-end encrypted cloud storage - Proton Drive • AdSpecial offer: 40% Off Yearly / 80% Off First Month. Protect your most important files, photos, and documents from prying eyes.
- Code for "DPOT: Auto-Regressive Denoising Operator Transformer for Large-Scale PDE Pre-Training"☆72Jun 10, 2024Updated 2 years ago
- [ICML 2024] Official PyTorch implementation of the Vectorized Conditional Neural Field.☆18Aug 1, 2024Updated 2 years ago
- ☆14Aug 22, 2024Updated 2 years ago
- This repository is the official implementation of the paper Convolutional Neural Operators for robust and accurate learning of PDEs☆228Nov 24, 2025Updated 9 months ago
- [ICLR 2023] Factorized Fourier Neural Operators☆196Oct 13, 2023Updated 2 years ago
- [Neurips 2024] A benchmark suite for autoregressive neural emulation of PDEs. (≥46 PDEs in 1D, 2D, 3D; Differentiable Physics; Unrolled T…☆108Jun 1, 2026Updated 3 months ago
- Code for Characterizing Scaling and Transfer Learning Behavior of FNO in SciML☆55May 31, 2023Updated 3 years ago
- Multiwavelets-based operator model☆70Feb 16, 2022Updated 4 years ago
- ☆69Jul 10, 2023Updated 3 years ago
- Wordpress hosting with auto-scaling - Free Trial Offer • AdFully Managed hosting for WordPress and WooCommerce businesses that need reliable, auto-scalable performance. Cloudways SafeUpdates now available.
- [NeurIPS 23] Official Code for "Learning Efficient Surrogate Dynamic Models with Graph Spline Networks"☆16Jul 19, 2024Updated 2 years ago
- ☆28Jul 17, 2025Updated last year
- Training methodologies for autoregressive neural operators/emulators in JAX.☆15Jun 1, 2026Updated 3 months ago
- Benchmarking Autoregressive Conditional Diffusion Models for Turbulent Flow Simulation☆118Dec 13, 2024Updated last year
- A comprehensive benchmark for machine learning multiphysics flows☆21Feb 3, 2026Updated 6 months ago
- ENMA: Tokenwise Autoregression for Generative Neural PDE Operators☆19Mar 19, 2026Updated 5 months ago
- Code for the paper "Poseidon: Efficient Foundation Models for PDEs"☆195Apr 10, 2025Updated last year
- Inducing Point Operator Transformer: A Flexible and Scalable Architecture for Solving PDEs (AAAI 2024)☆14Jul 30, 2024Updated 2 years ago
- ☆24Mar 3, 2023Updated 3 years ago
- GPU virtual machines on DigitalOcean Gradient AI • AdGet to production fast with high-performance AMD and NVIDIA GPUs you can spin up in seconds. The definition of operational simplicity.
- A Library for Advanced Neural PDE Solvers.☆336Mar 10, 2026Updated 5 months ago
- ☆16Mar 3, 2023Updated 3 years ago
- Code for orthogonal neural operator☆17Oct 15, 2023Updated 2 years ago
- Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting☆51Nov 24, 2023Updated 2 years ago
- ☆16Nov 20, 2023Updated 2 years ago
- ☆17May 1, 2022Updated 4 years ago
- ☆62Jul 21, 2025Updated last year