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2026 AI/ML internship & new graduate job list updated daily
Variational Physic-informed Neural Operator (VINO) for Learning Partial Differential Equations
About code release of "Transolver: A Fast Transformer Solver for PDEs on General Geometries", ICML 2024 Spotlight. https://arxiv.org/abs/2402.02366
A PyTorch library for implementing flow matching algorithms, featuring continuous and discrete flow matching implementations. It includes practical examples for both text and image modalities.
PyTorch implementation of the diffusion-based method for CFD data super-resolution proposed in the paper "A Physics-informed Diffusion Model for High-fidelity Flow Field Reconstruction".
[NeurIPS 2025] Geometry Aware Operator Transformer As An Efficient And Accurate Neural Surrogate For PDEs On Arbitrary Domains
[SIGGRAPH 2025] 3D Stylization via Large Reconstruction Model
Collection of advice for prospective and current PhD students
redbKIT is a MATLAB library for reduced-order modeling of parametrized PDEs
A latent text-to-image diffusion model
Use Fourier transform to learn operators in differential equations.
Pytorch implementation of SIREN - Implicit Neural Representations with Periodic Activation Function
This repository collates a number of MATLAB examples demonstrating Scientific Machine Learning (SciML) and Physics Informed Machine Learning.
Multi-physics Optimization Research and Innovation System