Pinned Repositories
1024-bit-primes
Rust code to generate 1024-bit primes
AxisKeys.jl
🎹
BetterExp.jl
A faster and more accurate Exp (and Exp2, Exp10) functions for Julia.
db-benchmark
reproducible benchmark of database-like ops
Disease-Gene-Network-Analysis
Place for code for 2019 Comps
julia
The Julia Language: A fresh approach to technical computing.
lc0
The rewritten engine, originally for tensorflow. Now all other backends have been ported here.
leela_lite
Numerical-Final-Project
Trans-America
transamerica AI
oscardssmith's Repositories
oscardssmith/1024-bit-primes
Rust code to generate 1024-bit primes
oscardssmith/julia
The Julia Language: A fresh approach to technical computing.
oscardssmith/ArrayInterface.jl
Designs for new Base array interface primitives, used widely through scientific machine learning (SciML) and other organizations
oscardssmith/BoundaryValueDiffEq.jl
Boundary value problem (BVP) solvers for scientific machine learning (SciML)
oscardssmith/Cassette.jl
Overdub Your Julia Code
oscardssmith/CUDA.jl
CUDA programming in Julia.
oscardssmith/Dictionaries.jl
An alternative interface for dictionaries in Julia, for improved productivity and performance
oscardssmith/DiffEqBase.jl
The lightweight Base library for shared types and functionality for defining differential equation and scientific machine learning (SciML) problems
oscardssmith/DiffEqCallbacks.jl
A library of useful callbacks for hybrid scientific machine learning (SciML) with augmented differential equation solvers
oscardssmith/DiffEqDevMaterials
Various developer materials, like PDFs, notes, derivations, etc. for differential equations and scientific machine learning (SciML)
oscardssmith/DifferentialEquations.jl
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.
oscardssmith/EasyModelAnalysis.jl
High level functions for analyzing the output of simulations
oscardssmith/Enzyme.jl
Julia bindings for the Enzyme automatic differentiator
oscardssmith/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.
oscardssmith/FastBroadcast.jl
oscardssmith/Ferrite.jl
Finite element toolbox for Julia
oscardssmith/FixedSizeArrays.jl
oscardssmith/hash-prospector
Automated integer hash function discovery
oscardssmith/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)
oscardssmith/LinearSolve.jl
LinearSolve.jl: High-Performance Unified Linear Solvers
oscardssmith/LoweredCodeUtils.jl
Tools for manipulating Julia's lowered code
oscardssmith/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
oscardssmith/NonlinearSolve.jl
High-performance and differentiation-enabled nonlinear solvers
oscardssmith/OrdinaryDiffEq.jl
High performance differential equation solvers for ordinary differential equations, including neural ordinary differential equations (neural ODEs) and scientific machine learning (SciML)
oscardssmith/SciMLBase.jl
The Base interface of the SciML ecosystem
oscardssmith/SciMLBenchmarks.jl
Scientific machine learning (SciML) benchmarks, AI for science, and (differential) equation solvers. Covers Julia, Python (PyTorch, Jax), MATLAB, R
oscardssmith/SnoopCompile.jl
Making packages work faster with more extensive precompilation
oscardssmith/StructArrays.jl
Efficient implementation of struct arrays in Julia
oscardssmith/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
oscardssmith/Symbolics.jl
Symbolic programming for the next generation of numerical software