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 2 months ago
• probabilisticai / probai-2022
  Materials of the Nordic Probabilistic AI School 2022.
  ☆180Updated 3 years ago
• probabilisticai / probai-2021
  Materials of the Nordic Probabilistic AI School 2021.
  ☆93Updated 4 years 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…
  ☆58Updated 2 years ago
• ilkhem / icebeem
  Code for ICE-BeeM paper - NeurIPS 2020
  ☆87Updated 4 years ago
• EmilienDupont / neural-processes
  Pytorch implementation of Neural Processes for functions and images
  ☆234Updated 3 years ago
• rbardenet / bml-course
  Public repo for course material on Bayesian machine learning at ENS Paris-Saclay and Univ Lille
  ☆92Updated 8 months ago
• yataobian / awesome-ebm
  Collecting research materials on EBM/EBL (Energy Based Models, Energy Based Learning)
  ☆350Updated 4 months ago
• csquires / 6.S091-causality
  ☆191Updated 2 years ago
• LukasRinder / normalizing-flows
  Implementation of normalizing flows in TensorFlow 2 including a small tutorial.
  ☆147Updated last month
• probabilisticai / probai-2023
  Materials of the Nordic Probabilistic AI School 2023.
  ☆91Updated 2 years ago
• YannDubs / Neural-Process-Family
  Code for the Neural Processes website and replication of 4 papers on NPs. Pytorch implementation.
  ☆226Updated last year
• dobriban / Topics-In-Modern-Statistical-Learning
  Materials for STAT 991: Topics In Modern Statistical Learning (UPenn, 2022 Spring) - uncertainty quantification, conformal prediction, ca…
  ☆176Updated last year
• florist-notes / CS228_PGM
  🌲 Stanford CS 228 - Probabilistic Graphical Models
  ☆148Updated last year
• alisiahkoohi / Langevin-dynamics
  Sampling with gradient-based Markov Chain Monte Carlo approaches
  ☆108Updated last year
• izmailovpavel / understandingbdl
  ☆251Updated 2 years ago
• automl / TransformersCanDoBayesianInference
  Official Implementation of "Transformers Can Do Bayesian Inference", the PFN paper
  ☆239Updated last year
• georgiosarvanitidis / geometric_ml
  This repository contains code for applying Riemannian geometry in machine learning.
  ☆78Updated 4 years ago
• tengyuma / cs229m_notes
  ☆239Updated 2 years ago
• acmi-lab / cmu-10732-robustness-adaptivity-shift
  Official repository for CMU Machine Learning Department's 10732: Robustness and Adaptivity in Shifting Environments
  ☆75Updated 2 years ago
• GAMES-UChile / The_Art_of_Gaussian_Processes
  ☆39Updated 3 years ago
• chrhenning / hypnettorch
  Package for working with hypernetworks in PyTorch.
  ☆131Updated 2 years ago
• microsoft / otdd
  Optimal Transport Dataset Distance
  ☆173Updated 3 years ago
• bayinf / awesome-variational-inference
  A curated list of awesome variational inference
  ☆26Updated 5 years ago
• aleximmer / Laplace
  Laplace approximations for Deep Learning.
  ☆527Updated 7 months ago
• ex4sperans / variational-inference-with-normalizing-flows
  Reimplementation of Variational Inference with Normalizing Flows (https://arxiv.org/abs/1505.05770)
  ☆238Updated 7 years ago
• tonyduan / normalizing-flows
  Neural Spline Flow, RealNVP, Autoregressive Flow, 1x1Conv in PyTorch.
  ☆281Updated last year
• coallaoh / Principles
  ☆219Updated last year
• ilkhem / iVAE
  VAEs and nonlinear ICA: a unifying framework
  ☆39Updated 5 years ago
• vveitch / causality-tutorials
  Short tutorials on the use of machine learning methods for causal inference
  ☆49Updated 3 years ago