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A Python implementation of global optimization with gaussian processes.

Source code for Bayesian Optimization in Action, published by Manning

The fastest and most memory efficient lattice Boltzmann CFD software, running on all GPUs and CPUs via OpenCL. Free for non-commercial use.

Codebase for PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs.

Omnipose: a high-precision solution for morphology-independent cell segmentation

A natural language interface for computers

A reference containing Styles and Keywords that you can use with MidJourney AI. There are also pages showing resolution comparison, image weights, and much more!

Simple OOP Python Code to run some Pseudo-Spectral 2D Simulations of Turbulence

This repository contains python based LES solver (FDM/spectral) of 2D decaying turbulence.

Code accompanying "Inverse-Dirichlet Weighting Enables Reliable Training of Physics Informed Neural Networks", Maddu et al., 2021

Solve forward and inverse problems related to partial differential equations using finite basis physics-informed neural networks (FBPINNs)

PyTorch learning rate scheduler CosineAnnealingWarmRestarts with initial linear warmup for n steps followed by wight decay in consecutive cycles

Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more

Hidden Fluid Mechanics

A pytorch implementaion of physics informed neural networks for two dimensional NS equation

Physics Informed Deep Learning: Data-driven Solutions and Discovery of Nonlinear Partial Differential Equations