Alternatives and similar repositories for EigenPro3

Users that are interested in EigenPro3 are comparing it to the libraries listed below

• team-approx-bayes / ivon
  IVON optimizer for neural networks based on variational learning.
  ☆81Updated last year
• joneswack / dp-rfs
  This repository contains PyTorch implementations of various random feature maps for dot product kernels.
  ☆22Updated last year
• f-dangel / curvlinops
  PyTorch linear operators for curvature matrices (Hessian, Fisher/GGN, KFAC, ...)
  ☆62Updated this week
• runame / laplace-refinement
  Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks
  ☆10Updated 3 years ago
• frgsimpson / kitt
  Kernel Identification Through Transformers
  ☆14Updated 2 years ago
• aradha / recursive_feature_machines
  ☆61Updated 9 months ago
• franciscovargas / GP_Sinkhorn
  GP Sinkhorn Implementation, paper: https://www.mdpi.com/1099-4300/23/9/1134
  ☆23Updated 3 years ago
• google-deepmind / annealed_flow_transport
  ☆52Updated 2 years ago
• facebookresearch / w2ot
  Euclidean Wasserstein-2 optimal transportation
  ☆46Updated 2 years ago
• wiseodd / pub-ready-plots
  Agustinus' very opiniated publication-ready plotting library
  ☆71Updated 9 months ago
• bunnech / jkonet
  Proximal Optimal Transport Modeling of Population Dynamics (AISTATS 2022)
  ☆22Updated 2 years ago
• april-tools / cirkit
  a python framework to build, learn and reason about probabilistic circuits and tensor networks
  ☆133Updated this week
• PGM-Lab / 2023-ProbAI
  Repo for the Tutorials of Day1-Day2 of the Nordic Probabilistic AI School 2023
  ☆17Updated 2 years ago
• modichirag / GSM-VI
  Code for Gaussian Score Matching Variational Inference
  ☆35Updated 11 months ago
• federicobergamin / riemannian-laplace-approximation
  Repository for the paper "Riemannian Laplace approximations for Bayesian neural networks"
  ☆12Updated 2 years ago
• andres-fr / skerch
  Sketched linear operations for PyTorch
  ☆100Updated 3 months ago
• tml-epfl / sgd-sparse-features
  SGD with large step sizes learns sparse features [ICML 2023]
  ☆33Updated 2 years ago
• ruqizhang / discrete-langevin
  ☆42Updated 3 years ago
• alisiahkoohi / Langevin-dynamics
  Sampling with gradient-based Markov Chain Monte Carlo approaches
  ☆109Updated last year
• AndyShih12 / mac
  PyTorch implementation for "Training and Inference on Any-Order Autoregressive Models the Right Way", NeurIPS 2022 Oral, TPM 2023 Best Pa…
  ☆15Updated 2 years ago
• J-zin / energy-discrepancy
  NeurIPS'23: Energy Discrepancies: A Score-Independent Loss for Energy-Based Models
  ☆17Updated last year
• lgresele / independent-mechanism-analysis
  Code for the paper: "Independent mechanism analysis, a new concept?"
  ☆25Updated 2 years ago
• aradha / agop_feature_learning
  ☆17Updated last year
• cyz-ai / neural-approx-ss-lfi
  Codes for ICLR 21 paper: Neural Approximate Sufficient Statistics for Implicit Models
  ☆20Updated 3 years ago
• locuslab / edge-of-stability
  ☆73Updated last year
• aradha / deep_neural_feature_ansatz
  Code for verifying deep neural feature ansatz
  ☆21Updated 2 years ago
• aradha / lin-RFM
  Code for lin-RFM used for sparse recovery tasks
  ☆15Updated 10 months ago
• cooper-org / cooper
  A general-purpose, deep learning-first library for constrained optimization in PyTorch
  ☆152Updated 2 months ago
• runame / laplace-redux
  Laplace Redux -- Effortless Bayesian Deep Learning
  ☆44Updated 8 months ago
• tfjgeorge / nngeometry
  {KFAC,EKFAC,Diagonal,Implicit} Fisher Matrices and finite width NTKs in PyTorch
  ☆219Updated this week