Alternatives and similar repositories for Murphy-Machine-Learning-A-Probabilistic-Perspective-Errata-and-Notes-4th-printing:

Users that are interested in Murphy-Machine-Learning-A-Probabilistic-Perspective-Errata-and-Notes-4th-printing are comparing it to the libraries listed below

• MLaPP-Solution-Manual / Solutions-to-Machine-Learning-A-Probabilistic-Perspective-
  Solutions to "Machine Learning: A Probabilistic Perspective"
  ☆157Updated 3 years ago
• joanbruna / MathsDL-spring19
  Mathematics of Deep Learning, Courant Insititute, Spring 19
  ☆273Updated 5 years ago
• yousuketakada / prml_errata
  More PRML Errata
  ☆80Updated 2 years ago
• tqchen / ML-SGHMC
  Experiment code for Stochastic Gradient Hamiltonian Monte Carlo
  ☆105Updated 6 years ago
• mcgrady20150318 / BayesianNeuralNetwork
  a repo sharing Bayesian Neural Network recent papers
  ☆215Updated 5 years ago
• otokonoko8 / deep-Bayesian-nonparametrics-papers
  The collection of papers about combining deep learning and Bayesian nonparametrics
  ☆119Updated 5 years ago
• wiseodd / probabilistic-models
  Collection of probabilistic models and inference algorithms
  ☆241Updated 4 years ago
• otokonoko8 / implicit-variational-inference
  The collection of recent papers about variational inference
  ☆85Updated 5 years ago
• jamesmcinerney / vbmm
  Variational inference for Gaussian mixture models
  ☆34Updated 11 years ago
• mlss-2019 / slides
  ☆259Updated 5 years ago
• t-vi / candlegp
  Gaussian Processes in Pytorch
  ☆75Updated 4 years ago
• duvenaud / learn-discrete
  Graduate topics course on learning discrete latent structure.
  ☆66Updated 6 years ago
• rmgarnett / cse515t
  Materials for Bayesian Methods in Machine Learning Course
  ☆88Updated last month
• ivannz / mlss2019-bayesian-deep-learning
  MLSS2019 Tutorial on Bayesian Deep Learning
  ☆92Updated 5 years ago
• abdulfatir / normalizing-flows
  Understanding normalizing flows
  ☆131Updated 5 years ago
• mlss-2019 / tutorials
  ☆274Updated 4 years ago
• ermongroup / a-nice-mc
  Code for "A-NICE-MC: Adversarial Training for MCMC"
  ☆126Updated 6 years ago
• JeanKossaifi / caltech-tutorial
  Material for my Caltech tutorial on deep learning and tensor methods
  ☆69Updated 6 years ago
• google-deepmind / mc_gradients
  ☆163Updated 5 months ago
• yaroslavvb / kfac_pytorch
  ☆132Updated 7 years ago
• stats385 / stats385.github.io
  STATS385 course website
  ☆89Updated 2 years ago
• blei-lab / ars-reparameterization
  Source code for Naesseth et. al. "Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms" (2017)
  ☆39Updated 7 years ago
• vincentherrmann / wasserstein-notebook
  Wasserstein / earth mover's distance visualizations
  ☆66Updated 7 years ago
• shuangxu96 / IntroVB
  An introduction to variational Bayesian
  ☆24Updated 6 years ago
• ganguli-lab / deepchaos
  Experiments for the paper "Exponential expressivity in deep neural networks through transient chaos"
  ☆70Updated 8 years ago
• leelabcnbc / book-notes
  a bunch of notes about machine learning, image statistics, theoretical neuroscience, etc.
  ☆47Updated 6 years ago
• ssydasheng / Neural-Kernel-Network
  Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326
  ☆71Updated 6 years ago
• oxcsml / ML_bazaar
  OxCSML research group reading groups and meetings at the Department of Statistics, University of Oxford.
  ☆92Updated 3 years ago