mathurinm / andersoncdLinks
This code is no longer maintained. The codebase has been moved to https://github.com/scikit-learn-contrib/skglm. This repository only serves to reproduce the results of the AISTATS 2021 paper "Anderson acceleration of coordinate descent" by Quentin Bertrand and Mathurin Massias.
☆18Updated 2 years ago
Alternatives and similar repositories for andersoncd
Users that are interested in andersoncd are comparing it to the libraries listed below
Sorting:
- Fast hyperparameter settings for non-smooth estimators:☆40Updated 2 years ago
- PEPit is a package enabling computer-assisted worst-case analyses of first-order optimization methods.☆88Updated last week
- 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
- Source code for my PhD thesis: Backpropagation Beyond the Gradient☆20Updated 2 years ago
- Anderson accelerated Douglas-Rachford splitting☆29Updated 4 years ago
- An ultra-lightweight JAX implementation of sparse Gaussian processes via pathwise sampling.☆22Updated 4 years ago
- Proximal optimization in pure python☆118Updated 3 years ago
- Functional models and algorithms for sparse signal processing☆90Updated last year
- Efficient SDE samplers including Gaussian-based probabilistic solvers. Written in JAX.☆10Updated 5 months ago
- A Julia implementation of sparse Gaussian processes via path-wise doubly stochastic variational inference.☆33Updated 4 years ago
- Probabilistic solvers for differential equations in JAX. Adaptive ODE solvers with calibration, state-space model factorisations, and cus…☆49Updated 3 months ago
- Code for the Paper "Physics-Informed Gaussian Process Regression Generalizes Linear PDE Solvers"☆30Updated last year
- Kernel Stein Discrepancy Descent : a method to sample from unnormalized densities☆21Updated last year
- Making your benchmark of optimization algorithms simple and open☆264Updated this week
- ☆13Updated 5 months ago
- Tutorial materials of the Probabilistic Numerics Spring School.☆34Updated 2 years ago
- Probabilistic numerical finite differences. Compute finite difference weights and differentiation matrices on scattered data sites and wi…☆11Updated 2 years ago
- A generic interface for linear algebra backends☆73Updated 4 months ago
- El0ps: An Exact L0-Problem Solver☆12Updated last month
- Matrix-free linear algebra in JAX.☆126Updated last month
- A generic library for linear and non-linear Gaussian smoothing problems. The code leverages JAX and implements several linearization algo…☆12Updated 7 months ago
- Painless optimisation of constrained variables in AutoGrad, TensorFlow, PyTorch, and JAX☆23Updated 2 years ago
- A Tensorflow based library for Time Series Modelling with Gaussian Processes☆32Updated last year
- Gaussian processes with spherical harmonic features in JAX☆15Updated last year
- A framework for composing Neural Processes in Julia☆76Updated 4 years ago
- Public code for running Stochastic Gradient Descent on GPs.☆39Updated 2 months ago
- Approximate inference for Markov Gaussian processes using iterated Kalman smoothing, in JAX☆100Updated 2 years ago
- Pytorch implementation of SuperPolyak subgradient method.☆43Updated 2 years ago
- Chirp instantaneous frequency estimation using stochastic differential equation Gaussian processes☆12Updated 8 months ago
- Code for 'Periodic Activation Functions Induce Stationarity' (NeurIPS 2021)☆19Updated 3 years ago