EduardoMolina
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Open-source deep-learning framework for building, training, and fine-tuning deep learning models using state-of-the-art Physics-ML methods
A curated list of practical financial machine learning tools and applications.
Python code for "Probabilistic Machine learning" book by Kevin Murphy
NeuralFoil is a practical airfoil aerodynamics analysis tool using physics-informed machine learning, in pure Python/NumPy.
NASA's aircraft analysis, design, and optimization tool
Interpolation and function approximation with JAX
A differentiable PDE solving framework for machine learning
Curated list for ML in FM
Linear solvers in JAX and Equinox. https://docs.kidger.site/lineax
Python solutions to Fundamentals of Numerical Engineering Analysis 2nd edition
Core functions for the Julia (2nd) edition of the text Fundamentals of Numerical Computation, by Driscoll and Braun.
Course notes for a course based on R.J. LeVeque's "Finite Volume Methods for Hyperbolic Problems"
Spectral Navier Stokes (and similar) solvers in Python
An interactive book about the Riemann problem for hyperbolic PDEs, using Jupyter notebooks.
A course in numerical methods with Python for engineers and scientists: currently 5 learning modules, with student assignments.
Simple explicit compressible Euler solver for 3D unstructured polyhedral meshes written in Julia
GPU-Enabled, Zero-Copy AMReX Python Bindings including AI/ML
Mission Analysis plugin for OpenMDAO
P4est.jl is lightweight Julia wrapper for the p4est C library, which allows to manage multiple connected adaptive quadtrees/octrees in parallel.
A collection of CFD related resources for Taichi developers.
Elegant easy-to-use neural networks + scientific computing in JAX. https://docs.kidger.site/equinox/
A community supported Windows build for jax.
Minimal Implementation of Bayesian Optimization in JAX
A suite of benchmarks for CPU and GPU performance of the most popular high-performance libraries for Python 🚀
Kernel Independent Fast Multipole Method in Python