Alternatives and similar repositories for caltech-tutorial

Users that are interested in caltech-tutorial are comparing it to the libraries listed below

• ritchieng / eigenvectors-from-eigenvalues
  PyTorch implementation comparison of old and new method of determining eigenvectors from eigenvalues.
  ☆98Updated 3 years ago
• duvenaud / learn-discrete
  Graduate topics course on learning discrete latent structure.
  ☆67Updated 6 years ago
• conormdurkan / autoregressive-energy-machines
  Autoregressive Energy Machines
  ☆78Updated 2 years ago
• thegregyang / NNspectra
  Computing the eigenvalues of Neural Tangent Kernel and Conjugate Kernel (aka NNGP kernel) over the boolean cube
  ☆47Updated 5 years ago
• JeanKossaifi / ifi-summer-school
  Slides and notebooks for the IfI Summer School 2018 on Machine Learning
  ☆36Updated 7 years ago
• mblondel / fenchel-young-losses
  Probabilistic classification in PyTorch/TensorFlow/scikit-learn with Fenchel-Young losses
  ☆188Updated last year
• ssydasheng / Neural-Kernel-Network
  Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326
  ☆71Updated 7 years ago
• google-deepmind / mc_gradients
  ☆170Updated last year
• ericjang / nf-jax
  Normalizing Flows in Jax
  ☆107Updated 5 years ago
• golkar / backdrop
  Implementation and demonstration of backdrop in pytorch. Code and demonstration of GP dataset generator.
  ☆68Updated 7 years ago
• abdulfatir / normalizing-flows
  Understanding normalizing flows
  ☆132Updated 5 years ago
• xbresson / CE9010_2018
  Python notebooks and slides for CE9010: Introduction to Data Science, Semester 2 2017/18
  ☆52Updated 6 years ago
• andymiller / ReducedVarianceReparamGradients
  Reducing Reparameterization Gradient Variance code.
  ☆33Updated 8 years ago
• Sohl-Dickstein / Minimum-Probability-Flow-Learning
  Matlab code implementing Minimum Probability Flow Learning.
  ☆69Updated 10 years ago
• joanbruna / ir18
  Inference and Representation (DS-GA-1005, CSCI-GA.2569), fall 18
  ☆67Updated 6 years ago
• henripal / sgld
  ☆59Updated 6 years ago
• david-abel / icml_2019
  Notes for ICML 2019
  ☆38Updated 6 years ago
• lxuechen / BDMC
  PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.
  ☆52Updated 4 years ago
• cranmer / poisson-convolution-sum
  Implements an infinite sum of poisson-weighted convolutions
  ☆27Updated 7 years ago
• RuiShu / tensorsketch
  A lightweight library for tensorflow 2.0
  ☆66Updated 5 years ago
• wittawatj / kernel-gof
  NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.
  ☆67Updated 6 years ago
• vincentherrmann / wasserstein-notebook
  Wasserstein / earth mover's distance visualizations
  ☆66Updated 8 years ago
• gbaydin / difftorch
  A differentiation API for PyTorch
  ☆30Updated 5 years ago
• rhaps0dy / convnets-as-gps
  Code for "Deep Convolutional Networks as shallow Gaussian Processes"
  ☆39Updated 6 years ago
• microsoft / statopt
  Statistical adaptive stochastic optimization methods
  ☆32Updated 5 years ago
• PrincetonLIPS / randomized_telescopes
  Code for "Efficient optimization of loops and limits with randomized telescoping sums"
  ☆28Updated 6 years ago
• brain-research / l2hmc
  TensorFlow implementation for training MCMC samplers from the paper: Generalizing Hamiltonian Monte Carlo with Neural Network
  ☆183Updated 7 years ago
• brain-research / conv-sv
  The Singular Values of Convolutional Layers
  ☆72Updated 6 years ago
• uber-research / loss-change-allocation
  ☆61Updated 2 years ago
• wlwkgus / NoisyNaturalGradient
  Pytorch Implementation of paper "Noisy Natural Gradient as Variational Inference"
  ☆121Updated 6 years ago