Alternatives and similar repositories for andersoncd

Users that are interested in andersoncd are comparing it to the libraries listed below

• TheoGuyard / El0ps
  El0ps: An Exact L0-Problem Solver
  ☆11Updated 3 weeks ago
• QB3 / sparse-ho
  Fast hyperparameter settings for non-smooth estimators:
  ☆40Updated 2 years ago
• josephsalmon / OrganizationFiles
  ☆13Updated 4 months ago
• mathurinm / libsvmdata
  Python package to fetch data from the LIBSVM website.
  ☆20Updated 2 months ago
• cvxgrp / a2dr
  Anderson accelerated Douglas-Rachford splitting
  ☆29Updated 4 years ago
• benchopt / benchmark_lasso
  Benchopt benchmark for Lasso
  ☆14Updated last year
• pmelchior / proxmin
  Proximal optimization in pure python
  ☆118Updated 3 years ago
• pnkraemer / tornadox
  Probabilistic ODE solvers are fun, but are they fast? See also: https://github.com/pnkraemer/probdiffeq for JAX code or https://github.c…
  ☆21Updated 11 months ago
• PerformanceEstimation / PEPit
  PEPit is a package enabling computer-assisted worst-case analyses of first-order optimization methods.
  ☆88Updated 5 months ago
• alisaab / l0bnb
  Solves the best subset selection problem
  ☆44Updated 3 years ago
• gianlucadetommaso / Stein-variational-samplers
  Python and MATLAB code for Stein Variational sampling methods
  ☆25Updated 6 years ago
• pierreablin / ksddescent
  Kernel Stein Discrepancy Descent : a method to sample from unnormalized densities
  ☆21Updated last year
• yorkerlin / VB-MixEF
  Code for ICML 2019 paper on "Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family Approximations"
  ☆18Updated 4 years ago
• f-dangel / phd-thesis
  Source code for my PhD thesis: Backpropagation Beyond the Gradient
  ☆20Updated 2 years ago
• aterenin / SparseGaussianProcesses.jl
  A Julia implementation of sparse Gaussian processes via path-wise doubly stochastic variational inference.
  ☆33Updated 4 years ago
• svaiter / pyprox
  Proximal algorithms made easy in Python
  ☆59Updated 8 years ago
• jgorham / SteinDiscrepancy.jl
  Practical tools for quantifying how well a sample approximates a target distribution
  ☆27Updated 4 years ago
• aterenin / SparseGPAX
  An ultra-lightweight JAX implementation of sparse Gaussian processes via pathwise sampling.
  ☆22Updated 4 years ago
• eepperly / Randomly-Pivoted-Cholesky
  Code for the paper "Randomly pivoted Cholesky: Practical approximation of a kernel matrix with few entry evaluations"
  ☆29Updated 8 months ago
• wesselb / varz
  Painless optimisation of constrained variables in AutoGrad, TensorFlow, PyTorch, and JAX
  ☆23Updated 2 years ago
• spdes / chirpgp
  Chirp instantaneous frequency estimation using stochastic differential equation Gaussian processes
  ☆12Updated 8 months ago
• ylefay / bayesianSDEsolver
  Efficient SDE samplers including Gaussian-based probabilistic solvers. Written in JAX.
  ☆10Updated 5 months ago
• facebookresearch / RidgeSketch
  A Fast sketching based solver for large scale ridge regression
  ☆17Updated last year
• AdrienCorenflos / particle_mala
  Gradient-informed particle MCMC methods
  ☆12Updated last year
• JuliaFirstOrder / ProximalAlgorithms.jl
  Proximal algorithms for nonsmooth optimization in Julia
  ☆133Updated last month
• cambridge-mlg / sgd-gp
  Public code for running Stochastic Gradient Descent on GPs.
  ☆39Updated 2 months ago
• marvinpfoertner / linpde-gp
  Code for the Paper "Physics-Informed Gaussian Process Regression Generalizes Linear PDE Solvers"
  ☆30Updated last year
• ae-foster / pyro
  Deep universal probabilistic programming with Python and PyTorch
  ☆12Updated 5 years ago
• vienmai / drot
  Douglas-Rachford Splitting for Optimal Transport
  ☆10Updated 3 years ago
• ganguli-lab / proxalgs
  Proximal algorithms and operators in python
  ☆26Updated 6 years ago