Alternatives and similar repositories for Learning-Performance-Estimation:

Users that are interested in Learning-Performance-Estimation are comparing it to the libraries listed below

• PerformanceEstimation / Performance-Estimation-Toolbox
  Code of the Performance Estimation Toolbox (PESTO) whose aim is to ease the access to the PEP methodology for performing worst-case analy…
  ☆53Updated last year
• PerformanceEstimation / PEPit
  PEPit is a package enabling computer-assisted worst-case analyses of first-order optimization methods.
  ☆85Updated last month
• AccelerationMethods / AccelerationMonograph
  ☆12Updated 3 years ago
• facebookresearch / neural-scs
  Neural Fixed-Point Acceleration for Convex Optimization
  ☆29Updated 2 years ago
• cvxpy / cvxtorch
  Convert CVXPY expressions to PyTorch expressions
  ☆13Updated 4 months ago
• SaitejaUtpala / rieoptax
  Riemannian Optimization Using JAX
  ☆48Updated last year
• krishnap25 / sqwash
  Distributionally Robust Learning in PyTorch. Install with `pip install sqwash`.
  ☆12Updated last year
• cambridge-mlg / sgd-gp
  Public code for running Stochastic Gradient Descent on GPs.
  ☆36Updated 3 months ago
• QB3 / sparse-ho
  Fast hyperparameter settings for non-smooth estimators:
  ☆39Updated last year
• 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  This code is no longer maintained.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…
  ☆17Updated 2 years ago
• facebookresearch / SparseBO
  code associated with paper "Sparse Bayesian Optimization"
  ☆26Updated last year
• AaltoML / sequential-gp
  Code for 'Memory-based dual Gaussian processes for sequential learning' (ICML 2023)
  ☆12Updated last year
• stellatogrp / l2ws_qp
  ☆14Updated last year
• cvxgrp / diffcp
  Differentiation through cone programs
  ☆96Updated 2 weeks ago
• facebookresearch / rcpm
  Riemannian Convex Potential Maps
  ☆67Updated last year
• facebookresearch / LANCER
  Repo for the paper "Landscape Surrogate Learning Decision Losses for Mathematical Optimization Under Partial Information"
  ☆36Updated last year
• COR-OPT / SuperPolyak.py
  Pytorch implementation of SuperPolyak subgradient method.
  ☆43Updated 2 years ago
• sbanert / large-scale-material
  Material for the course Large-Scale Convex Optimisation at LTH, autumn 2020
  ☆14Updated 4 years ago
• AaltoML / PeriodicBNN
  Code for 'Periodic Activation Functions Induce Stationarity' (NeurIPS 2021)
  ☆18Updated 3 years ago
• moskomule / hypergrad
  Simple and extensible hypergradient for PyTorch
  ☆16Updated last year
• imbirik / LieStationaryKernels
  Supplementary code for the paper "Stationary Kernels and Gaussian Processes on Lie Groups and their Homogeneous Spaces"
  ☆42Updated last year
• antonioterpin / jkonet-star
  JAX implementation of the JKOnet* architecture presented in "Learning Diffusion at Lightspeed".
  ☆30Updated last month
• eepperly / Randomly-Pivoted-Cholesky
  Code for the paper "Randomly pivoted Cholesky: Practical approximation of a kernel matrix with few entry evaluations"
  ☆28Updated 4 months ago
• qsh-zh / pis
  [ICLR 2022] Path integral sampler
  ☆43Updated last year
• f-dangel / vivit
  [TMLR 2022] Curvature access through the generalized Gauss-Newton's low-rank structure: Eigenvalues, eigenvectors, directional derivative…
  ☆17Updated last year
• alpyurtsever / SketchyCGAL
  MATLAB implementation of the Scalable Semidefinite Programming
  ☆26Updated last year
• facebookresearch / lagrangian-ot
  Neural Optimal Transport with Lagrangian Costs
  ☆52Updated 7 months ago
• Sulam-Group / k-rcps
  "How to Trust Your Diffusion Models: A Convex Optimization Approach to Conformal Risk Control"
  ☆17Updated last year
• patrick-kidger / FasterNeuralDiffEq
  Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)
  ☆86Updated 2 years ago
• ghliu / mean-field-fcdnn
  ☆28Updated 5 years ago