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cgd

This repository contains the Julia code for the paper "Competitive Gradient Descent"

cholesky_by_kl_minimization

Sparse Cholesky factorization by Kullback-Leibler minimization

cmd_old

The julia code for the paper on Competitive Mirror Descent

compressingsolvers.jl

Code containing the package for compressing blackbox solvers

conditional_knn

a respository to explore the usefulness of the conditional knn estimator

f-t-s.github.io

A beautiful, simple, clean, and responsive Jekyll theme for academics

florianstyle.jl

h2pack

H2 Matrix Package

kolesky.jl

This package implements the methods described in https://arxiv.org/abs/2004.14455 for fast Gaussian process statistics

modular_cmd.jl

multi_cmd

Extending Competitive Mirror Descent to a multi-agent, reinforcement learning setting.

nearlinkernel

pinns

Physics Informed Deep Learning: Data-driven Solutions and Discovery of Nonlinear Partial Differential Equations

sparse_recovery_of_elliptic_solution_operators_from_matrix-vector_products

spelliptic

This repository contains an implementation of the sparse Cholesky factorization of dense covariance matrices as described in https://arxiv.org/abs/1706.02205