Vedant Puri's repositories
KolmogorovArnold.jl
Julia implementation of the Kolmogorov-Arnold network with custom gradients for fast training.
NeuralROMs.jl
SNF-ROM: Projection-based nonlinear reduced order modeling with smooth neural fields
FluxMPI.jl
Distributed Data Parallel Training of Deep Neural Networks
AbstractFFTs.jl
A Julia framework for implementing FFTs
awesome-kan
A comprehensive collection of KAN(Kolmogorov-Arnold Network)-related resources, including libraries, projects, tutorials, papers, and more, for researchers and developers in the Kolmogorov-Arnold Network field.
ComponentArrays.jl
Arrays with arbitrarily nested named components.
CUDA.jl
CUDA programming in Julia.
DiffEqBase.jl
The lightweight Base library for shared types and functionality for defining differential equation and scientific machine learning (SciML) problems
evidential-deep-learning
Learn fast, scalable, and calibrated measures of uncertainty using neural networks!
Flux.jl
Relax! Flux is the ML library that doesn't make you tensor
ForwardDiff.jl
Forward Mode Automatic Differentiation for Julia
GPUArrays.jl
Reusable array functionality for Julia's various GPU backends.
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)
ParameterSchedulers.jl
Common hyperparameter scheduling for ML
ProbNumDiffEq.jl
Probabilistic Numerical Differential Equation solvers via Bayesian filtering and smoothing
SciMLBase.jl
The Base interface of the SciML ecosystem
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.
SparseDiffTools.jl
Fast jacobian computation through sparsity exploitation and matrix coloring
StochasticDiffEq.jl
Solvers for stochastic differential equations which connect with the scientific machine learning (SciML) ecosystem