Stars
Experiments for understanding disentanglement in VAE latent representations
Curated list of some open-source codes for turbulent flow simulations, including turbulent multiphase, turbulent reacting flows, turbulent convection and turbulent atmospheric physics.
Ptera Software is a fast, easy-to-use, and open-source software package for analyzing flapping-wing flight.
A sequence of Jupyter notebooks featuring the "12 Steps to Navier-Stokes" http://lorenabarba.com/
NeuralFoil is a practical airfoil aerodynamics analysis tool using physics-informed machine learning, exposed to end-users in pure Python/NumPy.
This repo is a work in progress aimed at gathering useful open-source resources for CFD engineers in one place. It includes notes, scripts, and tutorials for tools like ParaView, Gmsh, and more. Th…
A Computational Fluid Dynamics (CFD) course with Python
React components for data visualization and exploration
A 15TB Collection of Physics Simulation Datasets
A learning rate range test implementation in PyTorch
Convert LibreOffice slides to PDF without losing animations
Code for the paper "Rational neural networks", NeurIPS 2020
Lightning-UQ-Box: Uncertainty Quantification for Neural Networks with PyTorch and Lightning
A professionally curated list of awesome Conformal Prediction videos, tutorials, books, papers, PhD and MSc theses, articles and open-source libraries.
Code accompanying The Lattice Boltzmann Method: Principles and Practice
For optimization algorithm research and development.
Schedule-Free Optimization in PyTorch
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
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 f…
Implementation of Unconstrained Monotonic Neural Network and the related experiments. These architectures are particularly useful for modelling monotonic transformations in normalizing flows.
beta-NLL introduced in our paper "On the Pitfalls of Heteroscedastic Uncertainty Estimation with Probabilistic Neural Networks" ICLR 2022
Library to help implement a complex-valued neural network (cvnn) using tensorflow as back-end
Open-source deep-learning framework for building, training, and fine-tuning deep learning models using state-of-the-art Physics-ML methods
😎 Curated list of awesome software for numerical analysis and scientific computing
A curated list of repositories related to fluid dynamics.