Alternatives and similar repositories for RidgeSketch

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

• alisaab / l0bnb
  Solves the best subset selection problem
  ☆46Updated 3 years ago
• josephsalmon / OrganizationFiles
  ☆13Updated 3 months ago
• QB3 / sparse-ho
  Fast hyperparameter settings for non-smooth estimators:
  ☆40Updated last year
• gowerrobert / StochOpt.jl
  A suite of stochastic optimization methods for solving the empirical risk minimization problem.
  ☆16Updated 5 years ago
• eepperly / Randomly-Pivoted-Cholesky
  Code for the paper "Randomly pivoted Cholesky: Practical approximation of a kernel matrix with few entry evaluations"
  ☆28Updated 7 months ago
• aterenin / SparseGaussianProcesses.jl
  A Julia implementation of sparse Gaussian processes via path-wise doubly stochastic variational inference.
  ☆33Updated 4 years ago
• pierrejacob / unbiasedmcmc
  Unbiased Markov chain Monte Carlo with couplings
  ☆29Updated 2 years ago
• aki-nishimura / discontinuous-hmc
  "Discontinuous Hamiltonian Monte Carlo for sampling discrete parameters" by Akihiko Nishimura, David Dunson, Jianfeng Lu
  ☆27Updated 6 years ago
• operalib / operalib
  Learning with operator-valued kernels
  ☆22Updated 2 years ago
• TheoGuyard / El0ps
  El0ps: An Exact L0-Problem Solver
  ☆9Updated last week
• eepperly / XTrace
  Code for the paper "XTrace: Making the most of every sample in stochastic trace estimation"
  ☆14Updated 2 years ago
• mathurinm / andersoncd
  This code is no longer maintained. The codebase has been moved to https://github.com/scikit-learn-contrib/skglm. This repository only ser…
  ☆18Updated 2 years ago
• joneswack / dp-rfs
  This repository contains PyTorch implementations of various random feature maps for dot product kernels.
  ☆21Updated 10 months ago
• gianlucadetommaso / Stein-variational-samplers
  Python and MATLAB code for Stein Variational sampling methods
  ☆25Updated 5 years ago
• wongswk / magi
  ☆14Updated 6 months ago
• lezcano / expm
  Differentiable and numerically stable implementation of the matrix exponential
  ☆33Updated 4 years ago
• Tom-Ryder / VIforSDEs
  A variational method for fast, approximate inference for stochastic differential equations.
  ☆44Updated 6 years ago
• sremes / nssm-gp
  Non-stationary spectral mixture kernels implemented in GPflow
  ☆28Updated 6 years ago
• jhuggins / viabel
  Efficient, lightweight variational inference and approximation bounds
  ☆43Updated last year
• ymalitsky / adaptive_GD
  Adaptive gradient descent without descent
  ☆47Updated 3 years ago
• jgorham / SteinDiscrepancy.jl
  Practical tools for quantifying how well a sample approximates a target distribution
  ☆27Updated 4 years ago
• justindomke / pangolin
  probabilistic programming focused on fun
  ☆40Updated 6 months ago
• jaanli / hierarchical-variational-models-physics
  Hierarchical variational models for physics.
  ☆17Updated 4 years ago
• ae-foster / dad
  Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design
  ☆31Updated 3 years ago
• udellgroup / orie7391
  Materials and syllabus for Cornell ORIE 7391, Faster: Algorithmic Ideas for Speeding Up Optimization
  ☆25Updated 3 years ago
• BasisResearch / millipede
  A library for bayesian variable selection
  ☆28Updated 3 months ago
• wesselb / lab
  A generic interface for linear algebra backends
  ☆73Updated 2 months ago
• kazukiosawa / ngd_in_wide_nn
  simple JAX-/NumPy-based implementations of NGD with exact/approximate Fisher Information Matrix both in parameter-space and function-spac…
  ☆14Updated 4 years ago
• pierrejacob / couplingsmontecarlo
  some scripts for the couplings enthusiasts!
  ☆32Updated 4 years ago
• abhiagwl / vistan
  A simple library to run variational inference on Stan models.
  ☆30Updated 2 years ago