openhackathons-org / End-to-End-AI-for-Science
This repository containts materials for End-to-End AI for Science
☆141Updated this week
Alternatives and similar repositories for End-to-End-AI-for-Science:
Users that are interested in End-to-End-AI-for-Science are comparing it to the libraries listed below
- Framework providing pythonic APIs, algorithms and utilities to be used with PhysicsNeMo core to physics inform model training as well as …☆232Updated last week
- Pytorch bindings for Fortran☆93Updated last year
- Applications of PINOs☆122Updated 2 years ago
- A library for directly calling PyTorch ML models from Fortran.☆111Updated this week
- This repository is the official project page of the course AI in the Sciences and Engineering, ETH Zurich.☆200Updated 5 months ago
- This repository is the official implementation of the paper Convolutional Neural Operators for robust and accurate learning of PDEs☆166Updated 6 months ago
- Code for the paper "Poseidon: Efficient Foundation Models for PDEs"☆139Updated 2 weeks ago
- Simple OOP Python Code to run some Pseudo-Spectral 2D Simulations of Turbulence☆64Updated 2 years ago
- Differentiable Fluid Dynamics Package☆395Updated this week
- Resources about Machine Learning for solving PDEs.☆57Updated last year
- An Online Deep Learning Interface for HPC programs on NVIDIA GPUs☆165Updated last week
- ☆295Updated last month
- Curated list for ML in FM☆201Updated last month
- PINN (Physics-Informed Neural Networks) on Navier-Stokes Equations☆95Updated 2 years ago
- ☆200Updated 3 years ago
- We propose a conservative physics-informed neural network (cPINN) on decompose domains for nonlinear conservation laws. The conservation …☆70Updated 2 years ago
- ☆47Updated last year
- A large-scale benchmark for machine learning methods in fluid dynamics☆187Updated 4 months ago
- Repo of optimized training recipes for accelerating PyTorch workflows of AI driven surrogates for physical systems☆58Updated last year
- Extended Physics-Informed Neural Networks (XPINNs): A Generalized Space-Time Domain Decomposition Based Deep Learning Framework for Nonli…☆190Updated 2 years ago
- Code for the paper "Thermodynamics-informed graph neural networks" published in IEEE Transactions on Artificial Intelligence (TAI).☆98Updated 8 months ago
- ☆26Updated 9 months ago
- ☆29Updated last year
- Spectral Neural Operator☆78Updated last year
- Graph Neural Networks (GNN) based solvers for Computational Fluid Dynamics (CFD)☆34Updated last year
- ☆116Updated 5 years ago
- Call python from fortran☆89Updated last year
- ETH Zürich AI in the Sciences and Engineering Master's course 2024☆30Updated 9 months ago
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆84Updated 4 years ago
- A library for dimensionality reduction on spatial-temporal PDE☆65Updated last year