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Multi-language suite for high-performance solvers of differential equations and scientific machine learning (SciML) components. Ordinary differential equations (ODEs), stochastic differential equations (SDEs), delay differential equations (DDEs), differential-algebraic equations (DAEs), and more in Julia.
An acausal modeling framework for automatically parallelized scientific machine learning (SciML) in Julia. A computer algebra system for integrated symbolics for physics-informed machine learning and automated transformations of differential equations
21st century AD
Symbolic programming for the next generation of numerical software
Curated decibans of Julia programming language.
Penumbra Color Theme
Automatically update function definitions in a running Julia session
Graph-based molecule modeling toolkit for cheminformatics
Working with time-dependent networks in Julia
A flexible Julia toolkit for high-dimensional cellular profiles
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