Avik Pal's repositories
academicpages.github.io
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
SciMLSensitivity.jl
A component of the DiffEq ecosystem for enabling sensitivity analysis for scientific machine learning (SciML). Optimize-then-discretize, discretize-then-optimize, and more for ODEs, SDEs, DDEs, DAEs, etc.
ArrayInterface.jl
Designs for new Base array interface primitives, used widely through scientific machine learning (SciML) and other organizations
BandedMatrices.jl
A Julia package for representing banded matrices
ComponentArrays.jl
Arrays with arbitrarily nested named components.
CUDA.jl
CUDA programming in Julia.
DelayDiffEq.jl
Delay differential equation (DDE) solvers in Julia for the SciML scientific machine learning ecosystem. Covers neutral and retarded delay differential equations, and differential-algebraic equations.
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
DiffEqFlux.jl
Universal neural differential equations with O(1) backprop, GPUs, and stiff+non-stiff DE solvers
Documenter.jl
A documentation generator for Julia.
GPUArrays.jl
Reusable array functionality for Julia's various GPU backends.
KernelAbstractions.jl
Heterogeneous programming in Julia
LossFunctions.jl
Julia package of loss functions for machine learning.
MLDatasets.jl
Utility package for accessing common Machine Learning datasets in Julia
NonlinearSolve.jl
High-performance and differentiation-enabled nonlinear solvers (Newton methods), bracketed rootfinding (bisection, Falsi), with sparsity and Newton-Krylov support.
OrdinaryDiffEq.jl
High performance differential equation solvers for ordinary differential equations, including neural ordinary differential equations (neural ODEs) and scientific machine learning (SciML)
SciMLBase.jl
The Base interface of the SciML ecosystem
SciMLBenchmarks.jl
Benchmarks for scientific machine learning (SciML) software and differential equation solvers
StochasticDiffEq.jl
Solvers for stochastic differential equations which connect with the scientific machine learning (SciML) ecosystem
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
Tracker.jl
Flux's ex AD