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
  ☆46Updated 4 months ago
• probabilisticai / probai-2021
  Materials of the Nordic Probabilistic AI School 2021.
  ☆93Updated 3 years ago
• probabilisticai / probai-2022
  Materials of the Nordic Probabilistic AI School 2022.
  ☆174Updated 2 years ago
• probabilisticai / probai-2023
  Materials of the Nordic Probabilistic AI School 2023.
  ☆89Updated last year
• GAMES-UChile / The_Art_of_Gaussian_Processes
  ☆39Updated 3 years ago
• YannDubs / Neural-Process-Family
  Code for the Neural Processes website and replication of 4 papers on NPs. Pytorch implementation.
  ☆211Updated 8 months ago
• bayinf / awesome-variational-inference
  A curated list of awesome variational inference
  ☆20Updated 4 years ago
• acmi-lab / cmu-10732-robustness-adaptivity-shift
  Official repository for CMU Machine Learning Department's 10732: Robustness and Adaptivity in Shifting Environments
  ☆73Updated 2 years ago
• izmailovpavel / understandingbdl
  ☆236Updated 2 years ago
• alisiahkoohi / Langevin-dynamics
  Sampling with gradient-based Markov Chain Monte Carlo approaches
  ☆97Updated 10 months ago
• dobriban / Topics-In-Modern-Statistical-Learning
  Materials for STAT 991: Topics In Modern Statistical Learning (UPenn, 2022 Spring) - uncertainty quantification, conformal prediction, ca…
  ☆166Updated 9 months ago
• PGM-Lab / probai-2021-pyro
  Repo for the Tutorials of Day1-Day3 of the Nordic Probabilistic AI School 2021 (https://probabilistic.ai/)
  ☆47Updated 3 years ago
• EmilienDupont / neural-processes
  Pytorch implementation of Neural Processes for functions and images
  ☆228Updated 3 years ago
• ruqizhang / csgmcmc
  Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning
  ☆93Updated 4 years ago
• tengyuma / cs229m_notes
  ☆222Updated 2 years ago
• kushagra06 / CS228_PGM
  🌀 Stanford CS 228 - Probabilistic Graphical Models
  ☆122Updated 6 years ago
• yataobian / awesome-ebm
  Collecting research materials on EBM/EBL (Energy Based Models, Energy Based Learning)
  ☆287Updated last year
• jambo6 / neuralRDEs
  Code for: "Neural Rough Differential Equations for Long Time Series", (ICML 2021)
  ☆115Updated 3 years ago
• cambridge-mlg / convcnp
  Implementation of the Convolutional Conditional Neural Process
  ☆121Updated 3 years ago
• rbardenet / bml-course
  Public repo for course material on Bayesian machine learning at ENS Paris-Saclay and Univ Lille
  ☆85Updated this week
• bobby-he / Neural_Tangent_Kernel
  ☆67Updated 5 years ago
• LukasRinder / normalizing-flows
  Implementation of normalizing flows in TensorFlow 2 including a small tutorial.
  ☆146Updated 5 months ago
• chrhenning / hypnettorch
  Package for working with hypernetworks in PyTorch.
  ☆122Updated last year
• TeaPearce / Bayesian_NN_Ensembles
  AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'
  ☆88Updated 4 years ago
• florist-notes / CS228_PGM
  🌲 Stanford CS 228 - Probabilistic Graphical Models
  ☆118Updated 5 months ago
• BorealisAI / continuous-time-flow-process
  PyTorch code of "Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows" (NeurIPS 2020)
  ☆47Updated 4 years ago
• tjoo512 / belief-matching-framework
  Belief matching framework official implementation
  ☆39Updated last year
• TyXe-BDL / TyXe
  ☆149Updated 2 years ago
• psanch21 / causal-flows
  ☆53Updated 6 months ago
• VectorInstitute / vbll
  Simple (and cheap!) neural network uncertainty estimation
  ☆61Updated last week