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Hossein Pourbozorg's Projects

diffeqbase.jl icon diffeqbase.jl

The lightweight Base library for shared types and functionality for defining differential equation and scientific machine learning (SciML) problems

diffeqflux.jl icon diffeqflux.jl

Universal neural differential equations with O(1) backprop, GPUs, and stiff+non-stiff DE solvers, demonstrating scientific machine learning (SciML) and physics-informed machine learning methods

distributions.jl icon distributions.jl

A Julia package for probability distributions and associated functions.

distributionsad.jl icon distributionsad.jl

Automatic differentiation of Distributions using Tracker, Zygote, ForwardDiff and ReverseDiff

enzyme.jl icon enzyme.jl

Julia bindings for the Enzyme automatic differentiator

julia icon julia

The Julia Programming Language

lux.jl icon lux.jl

Explicitly Parameterized Neural Networks in Julia

mkl.jl icon mkl.jl

Intel MKL linear algebra backend for Julia

optimization.jl icon optimization.jl

Local, global, and beyond optimization for scientific machine learning (SciML)

ordinarydiffeq.jl icon ordinarydiffeq.jl

High performance ordinary differential equation (ODE) and differential-algebraic equation (DAE) solvers, including neural ordinary differential equations (neural ODEs) and scientific machine learning (SciML)

scimlsensitivity.jl icon scimlsensitivity.jl

A component of the DiffEq ecosystem for enabling sensitivity analysis for scientific machine learning (SciML). Optimize-then-discretize, discretize-then-optimize, adjoint methods, and more for ODEs, SDEs, DDEs, DAEs, etc.

simplenonlinearsolve.jl icon simplenonlinearsolve.jl

Fast and simple nonlinear solvers for the SciML common interface. Newton, Broyden, Bisection, Falsi, and more rootfinders on a standard interface.

sinograms.jl icon sinograms.jl

Julia library for working with sinograms / tomography / Radon transform

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