Alternatives and similar repositories for probabilisticAI_tutorials

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

• chrisorm / pydata-2018
  ☆64Updated 7 years ago
• franrruiz / uivi
  Code for Unbiased Implicit Variational Inference (UIVI)
  ☆15Updated 6 years ago
• anirudh9119 / walkback_nips17
  Variational Walkback, NIPS'17
  ☆28Updated 8 years ago
• hardmaru / mdn_jax_tutorial
  Mixture Density Networks (Bishop, 1994) tutorial in JAX
  ☆61Updated 5 years ago
• pronobis / libspn-keras
  Library for learning and inference with Sum-product Networks utilizing TensorFlow 2.x and Keras
  ☆48Updated 3 months ago
• pbrakel / anica
  Adversarial Non-linear Independent Component Analysis
  ☆50Updated 8 years ago
• davidenitti / ML
  ☆11Updated 4 years ago
• probabilisticai / probai-2019
  Materials of the Nordic Probabilistic AI School 2019.
  ☆130Updated 5 years ago
• Sohl-Dickstein / Minimum-Probability-Flow-Learning
  Matlab code implementing Minimum Probability Flow Learning.
  ☆69Updated 11 years ago
• duvenaud / warped-mixtures
  Code for density estimation with nonparametric cluster shapes.
  ☆39Updated 9 years ago
• DanielTakeshi / MCMC_and_Dynamics
  Practice with MCMC methods and dynamics (Langevin, Hamiltonian, etc.)
  ☆42Updated 5 years ago
• andymiller / ReducedVarianceReparamGradients
  Reducing Reparameterization Gradient Variance code.
  ☆33Updated 8 years ago
• didriknielsen / ds3_abi_exercises
  Exercises for the Tutorial on Approximate Bayesian Inference at the Data Science Summer School 2018
  ☆22Updated 7 years ago
• mblondel / fenchel-young-losses
  Probabilistic classification in PyTorch/TensorFlow/scikit-learn with Fenchel-Young losses
  ☆193Updated 2 years ago
• wittawatj / kernel-mod
  NeurIPS 2018. Linear-time model comparison tests.
  ☆18Updated 5 years ago
• ExpectationMax / sklearn-jax-kernels
  Composable kernels for scikit-learn implemented in JAX.
  ☆45Updated 5 years ago
• JeanKossaifi / caltech-tutorial
  Material for my Caltech tutorial on deep learning and tensor methods
  ☆70Updated 7 years ago
• ericjang / nf-jax
  Normalizing Flows in Jax
  ☆107Updated 5 years ago
• KarenUllrich / binary-VAE
  A minimal implementation of a VAE with BinConcrete (relaxed Bernoulli) latent distribution in TensorFlow.
  ☆22Updated 5 years ago
• jameshensman / VFF
  Variational Fourier Features
  ☆85Updated 4 years ago
• wittawatj / kernel-gof
  NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.
  ☆67Updated 6 years ago
• ssydasheng / Neural-Kernel-Network
  Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326
  ☆71Updated 7 years ago
• thangbui / geepee
  A collection of Gaussian process models
  ☆30Updated 8 years ago
• kyunghyuncho / backprop-kalman-filter
  ☆45Updated 6 years ago
• chrisdxie / in-depth-VI-tutorial
  ☆11Updated 9 years ago
• jluttine / variational-bayes-book
  Open access book on variational Bayesian methods written collaboratively
  ☆28Updated 10 years ago
• duvenaud / learn-discrete
  Graduate topics course on learning discrete latent structure.
  ☆67Updated 6 years ago
• microsoft / vi-hds
  Variational inference for hierarchical dynamical systems
  ☆48Updated last year
• tbrx / compiled-inference
  Train neural networks to use as SMC and importance sampling proposals
  ☆24Updated 8 years ago
• yunjhongwu / Sticky-HDPHMM-demo
  Sticky hierarchical Dirichlet process hidden Markov model for time series denoising
  ☆50Updated 9 years ago