Oscar Smith's repositories
1024-bit-primes
Rust code to generate 1024-bit primes
BoundaryValueDiffEq.jl
Boundary value problem (BVP) solvers for scientific machine learning (SciML)
Cassette.jl
Overdub Your Julia Code
CUDA.jl
CUDA programming in Julia.
Dictionaries.jl
An alternative interface for dictionaries in Julia, for improved productivity and performance
DiffEqBase.jl
The lightweight Base library for shared types and functionality for defining differential equation and scientific machine learning (SciML) problems
DiffEqCallbacks.jl
A library of useful callbacks for hybrid scientific machine learning (SciML) with augmented differential equation solvers
DiffEqDevMaterials
Various developer materials, like PDFs, notes, derivations, etc. for differential equations and scientific machine learning (SciML)
EasyModelAnalysis.jl
High level functions for analyzing the output of simulations
ExponentialUtilities.jl
Fast and differentiable implementations of matrix exponentials, Krylov exponential matrix-vector multiplications ("expmv"), KIOPS, ExpoKit functions, and more. All your exponential needs in SciML form.
Ferrite.jl
Finite element toolbox for Julia
hash-prospector
Automated integer hash function discovery
JumpProcesses.jl
Build and simulate jump equations like Gillespie simulations and jump diffusions with constant and state-dependent rates and mix with differential equations and scientific machine learning (SciML)
LinearSolve.jl
LinearSolve.jl: High-Performance Unified Linear Solvers
LogExpFunctions.jl
Julia package for various special functions based on `log` and `exp`.
LoweredCodeUtils.jl
Tools for manipulating Julia's lowered code
ModelingToolkit.jl
A 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
NonlinearSolve.jl
High-performance and differentiation-enabled nonlinear solvers
OrdinaryDiffEq.jl
High performance differential equation solvers for ordinary differential equations, including neural ordinary differential equations (neural ODEs) and scientific machine learning (SciML)
Revise.jl
Automatically update function definitions in a running Julia session
SciMLBase.jl
The Base interface of the SciML ecosystem
SciMLBenchmarks.jl
Scientific machine learning (SciML) benchmarks, AI for science, and (differential) equation solvers. Covers Julia, Python (PyTorch, Jax), MATLAB, R
SnoopCompile.jl
Making packages work faster with more extensive precompilation
StaticArraysCore.jl
Interface package for StaticArrays.jl
StructArrays.jl
Efficient implementation of struct arrays in Julia
Sundials.jl
Julia interface to Sundials, including a nonlinear solver (KINSOL), ODE's (CVODE and ARKODE), and DAE's (IDA) in a SciML scientific machine learning enabled manner