Alternatives and similar repositories for MLMI

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

• cambridge-mlg / mphil-intro-module
  Jupyter notebooks on inference, regression and classification for MPhil students
  ☆55Updated 3 months ago
• probabilisticai / probai-2022
  Materials of the Nordic Probabilistic AI School 2022.
  ☆181Updated 3 years ago
• automl / TransformersCanDoBayesianInference
  Official Implementation of "Transformers Can Do Bayesian Inference", the PFN paper
  ☆244Updated last year
• probabilisticai / probai-2021
  Materials of the Nordic Probabilistic AI School 2021.
  ☆93Updated 4 years ago
• yataobian / awesome-ebm
  Collecting research materials on EBM/EBL (Energy Based Models, Energy Based Learning)
  ☆356Updated 5 months ago
• aleximmer / Laplace
  Laplace approximations for Deep Learning.
  ☆529Updated 8 months ago
• Harry24k / bayesian-neural-network-pytorch
  PyTorch implementation of bayesian neural network [torchbnn]
  ☆553Updated last year
• csquires / 6.S091-causality
  ☆194Updated 2 years ago
• tengyuma / cs229m_notes
  ☆240Updated 2 years ago
• probabilisticai / probai-2023
  Materials of the Nordic Probabilistic AI School 2023.
  ☆91Updated 2 years ago
• rbardenet / bml-course
  Public repo for course material on Bayesian machine learning at ENS Paris-Saclay and Univ Lille
  ☆92Updated 10 months ago
• konstantinos-p / Bayesian-Neural-Networks-Reading-List
  A primer on Bayesian Neural Networks. The aim of this reading list is to facilitate the entry of new researchers into the field of Bayesi…
  ☆57Updated 2 years ago
• eemlcommunity / PracticalSessions2021
  ☆64Updated 4 years ago
• EmilienDupont / neural-processes
  Pytorch implementation of Neural Processes for functions and images
  ☆234Updated 3 years ago
• dobriban / Topics-In-Modern-Statistical-Learning
  Materials for STAT 991: Topics In Modern Statistical Learning (UPenn, 2022 Spring) - uncertainty quantification, conformal prediction, ca…
  ☆177Updated last year
• YannDubs / Neural-Process-Family
  Code for the Neural Processes website and replication of 4 papers on NPs. Pytorch implementation.
  ☆227Updated last year
• AdamCobb / hamiltorch
  PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC) and inference in Bayesian neural networks
  ☆462Updated last year
• ilkhem / icebeem
  Code for ICE-BeeM paper - NeurIPS 2020
  ☆87Updated 4 years ago
• LukasRinder / normalizing-flows
  Implementation of normalizing flows in TensorFlow 2 including a small tutorial.
  ☆146Updated 3 months ago
• izmailovpavel / understandingbdl
  ☆251Updated 3 years ago
• alisiahkoohi / Langevin-dynamics
  Sampling with gradient-based Markov Chain Monte Carlo approaches
  ☆108Updated last year
• soroosh-rz / Bayesian-Methods-for-Machine-Learning
  Bayesian Methods for Machine Learning
  ☆65Updated 6 years ago
• tfjgeorge / nngeometry
  {KFAC,EKFAC,Diagonal,Implicit} Fisher Matrices and finite width NTKs in PyTorch
  ☆216Updated 2 weeks ago
• GAMES-UChile / The_Art_of_Gaussian_Processes
  ☆40Updated 3 weeks ago
• coallaoh / Principles
  ☆238Updated last week
• florist-notes / CS228_PGM
  🌲 Stanford CS 228 - Probabilistic Graphical Models
  ☆150Updated last year
• facebookincubator / flowtorch
  This library would form a permanent home for reusable components for deep probabilistic programming. The library would form and harness a…
  ☆311Updated 6 months ago
• ZIYU-DEEP / Awesome-Information-Bottleneck
  This is a curated list for Information Bottleneck Principle, in memory of Professor Naftali Tishby.
  ☆382Updated last year
• psanch21 / causal-flows
  ☆52Updated last year
• kwignb / NeuralTangentKernel-Papers
  Neural Tangent Kernel Papers
  ☆120Updated 11 months ago