titus-pinta

new-optimization-algorithms-for-neural-network-training-using-operator-splitting-techniques

Implementation of the algorithms presented in https:/arxiv.org

agda-stdlib

The Agda standard library

DiffEqFlux.jl

DifferentialEquations.jl + Flux.jl = Universal neural differential equations with O(1) backprop, GPUs, and stiff+non-stiff DE solvers

json_placeholder

melpa

Recipes and build machinery for the biggest Emacs package repo

papirus-icon-theme

Pixel perfect icon theme for Linux

Symbolics.jl

A fast and modern CAS for a fast and modern language.

titus-pinta

Config files for my GitHub profile.

papirus-icon-theme

Pixel perfect icon theme for Linux

melpa

Recipes and build machinery for the biggest Emacs package repo

titus-pinta/papirus-icon-theme

Pixel perfect icon theme for Linux

titus-pinta/melpa

Recipes and build machinery for the biggest Emacs package repo

titus-pinta/new-optimization-algorithms-for-neural-network-training-using-operator-splitting-techniques

Implementation of the algorithms presented in https:/arxiv.org

titus-pinta/Symbolics.jl

A fast and modern CAS for a fast and modern language.

titus-pinta/titus-pinta

Config files for my GitHub profile.

titus-pinta/json_placeholder

titus-pinta/agda-stdlib

The Agda standard library

titus-pinta/DiffEqFlux.jl

DifferentialEquations.jl + Flux.jl = Universal neural differential equations with O(1) backprop, GPUs, and stiff+non-stiff DE solvers