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ODIL (Optimizing a Discrete Loss) is a Python framework for solving inverse and data assimilation problems for partial differential equations.
A library for scientific machine learning and physics-informed learning
Code for loralib, an implementation of "LoRA: Low-Rank Adaptation of Large Language Models"
Model Context Protocol Servers
A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.
A differentiable PDE solving framework for machine learning
CFD-solver-agnostic deep reinforcement learning framework for computational fluid dynamics on HPC platforms
Open-source deep-learning framework for building, training, and fine-tuning deep learning models using state-of-the-art Physics-ML methods
Pocket Flow: Codebase to Tutorial
Lightweight coding agent that runs in your terminal
Universal, autodiff-native software components for Simulation Intelligence. 📦
Flow solver for Darcy convection, based on the Advanced Finite Difference code AFiD
Decaying homogeneous isotropic turbulence simulated with WaterLily
Fast and simple fluid simulator in Julia
Library for communication between Fortran and Redis database
Sphinx theme from Read the Docs
HORSES3D: A high-order discontinuous Galerkin solver for flow simulations and multi-physics applications
Exascale simulation of multiphase/physics fluid dynamics