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airfrans

In this repository, you will find the different python scripts to train the available models on the AirfRANS dataset proposed at the NeurIPS 2022 Datasets and Benchmarks Track conference.

airfrans_lib

The AirfRANS dataset makes available numerical resolutions of the incompressible Reynolds-Averaged Navier–Stokes (RANS) equations over the NACA 4 and 5 digits series of airfoils and in a subsonic flight regime setup.

awesome-neural-ode

A collection of resources regarding the interplay between differential equations, deep learning, dynamical systems, control and numerical methods.

bootcamp

Bootcamp notebooks

camlab-dlsctutorials

climsim

An open large-scale dataset for training high-resolution physics emulators in hybrid multi-scale climate simulators.

computational-science-and-engineering

18.085 Gilbert Strang Computational Science and Engineering

cs224n-win2223

Code and written solutions of the assignments of the Stanford CS224N: Natural Language Processing with Deep Learning course from winter 2022/2023

deepmind-research

This repository contains implementations and illustrative code to accompany DeepMind publications

deepxde

A library for scientific machine learning and physics-informed learning

dlsc-2023

ETH Zürich Deep Learning in Scientific Computing Master's course 2023

dlsc_deepthermal

Project using deep learning to model thermal storage for solar panels

dlsc_projects

This repository contains the machine learning projects completed for the class "Deep Learning in Scientific Computing" taught at ETH jointly by Siddhartha Mishra and Benjamin Moseley in Spring 2024. The description of the tasks can be found in the PDFs.

dlsc_tasks

Repository for the Deep Learning in Scientific Computing course offered in Spring 2022 at ETH Zürich: Deep learning project with the aim of studying the preliminary design of a thermal energy storage.

drlfoam

Deep reinforcement learning with OpenFOAM

fastvpinns

FastVPINNs - A tensor-driven acceleration of VPINNs for complex geometries

gano

geo-fno

Geometry-Aware Fourier Neural Operator (Geo-FNO)

gradientamr

This project shows how to use the gradient of flow variables as a criteria to control Adaptive Mesh Refinement (AMR) for OpenFOAM simulations.

graph-pde

Using graph network to solve PDEs

jaxpi

lips

lorenz96

Understanding Lorentz96 One and Two layer systems

lpinns

failure modes in training of physics informed neural networks, a Lagrangian architecture is designed to conform to the direction of travel of information in convection-diffusion equations, i.e., method of characteristic; The repository includes a pytorch implementation of PINN and proposed LPINN with periodic boundary conditions

markov_neural_operator

mlfoam

Thoughts about ML committee for OpenFOAM

modulus

Open-source deep-learning framework for building, training, and fine-tuning deep learning models using state-of-the-art Physics-ML methods

naca_simulation

Python scripts to run resolution of the Reynolds-Averaged-Navier-Stokes equations over NACA 4 and 5 digits airfoils.

neural-ode

Jupyter notebook with Pytorch implementation of Neural Ordinary Differential Equations

neural-spdes

Neural Stochastic PDEs: resolution-invariant modelling of continuous spatiotemporal dynamics