Alternatives and similar repositories for phd-thesis-sample

Users that are interested in phd-thesis-sample are comparing it to the libraries listed below

• emtiyaz / vmp-for-svae
  Variational Message Passing for Structured VAE (Code for ICLR 2018 paper)
  ☆45Updated 7 years ago
• t-vi / candlegp
  Gaussian Processes in Pytorch
  ☆75Updated 5 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
• DanielTakeshi / MCMC_and_Dynamics
  Practice with MCMC methods and dynamics (Langevin, Hamiltonian, etc.)
  ☆42Updated 5 years ago
• duvenaud / learn-discrete
  Graduate topics course on learning discrete latent structure.
  ☆67Updated 6 years ago
• epfl-lts2 / pyunlocbox
  A Python convex optimization package using proximal splitting methods
  ☆116Updated last month
• jeanfeydy / global-divergences
  MMD, Hausdorff and Sinkhorn divergences scaled up to 1,000,000 samples.
  ☆57Updated 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
• rhaps0dy / convnets-as-gps
  Code for "Deep Convolutional Networks as shallow Gaussian Processes"
  ☆39Updated 6 years ago
• convnets-as-gps / convnets-as-gps
  Code for "Deep Convolutional Networks as shallow Gaussian Processes"
  ☆16Updated 6 years ago
• duvenaud / phd-thesis
  I am in [research] stepped in so far that, should I wade no more, Returning were as tedious as go o'er. -MacBeth
  ☆187Updated 11 years ago
• oxcsml / ML_bazaar
  OxCSML research group reading groups and meetings at the Department of Statistics, University of Oxford.
  ☆93Updated 3 years ago
• wittawatj / kernel-gof
  NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.
  ☆67Updated 6 years ago
• kekeblom / DeepCGP
  Deep convolutional gaussian processes.
  ☆80Updated 6 years ago
• alshedivat / DeterminantalPointProcesses.jl
  Determinantal Point Processes in Julia
  ☆12Updated 5 years ago
• tfrerix / proxprop
  Proximal Backpropagation - a neural network training algorithm that takes implicit instead of explicit gradient steps
  ☆42Updated 6 years ago
• davmre / gprf
  Gaussian Process Random Fields
  ☆21Updated 9 years ago
• gpapamak / epsilon_free_inference
  Code for paper "Fast ε-free Inference of Simulation Models with Bayesian Conditional Density Estimation"
  ☆32Updated 6 years ago
• abdulfatir / normalizing-flows
  Understanding normalizing flows
  ☆132Updated 5 years ago
• HIPS / author-roulette
  LaTeX package for randomizing author order based on a public seed.
  ☆40Updated 10 years ago
• YingzhenLi / Dropout_BBalpha
  Implementations of the ICML 2017 paper (with Yarin Gal)
  ☆38Updated 7 years ago
• josipd / torch-submod
  A PyTorch library for differentiable submodular minimization.
  ☆57Updated 7 years ago
• RobRomijnders / bayes_nn
  Uncertainty interpretations of the neural network
  ☆32Updated 7 years ago
• BiuBiuBiLL / InfoFeatureSelection
  Variational Information Maximization for Feature Selection
  ☆11Updated 9 years ago
• emtiyaz / vadam
  Code for ICML 2018 paper on "Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam" by Khan, Nielsen, Tangkaratt, Lin, …
  ☆112Updated 6 years ago
• mblondel / fenchel-young-losses
  Probabilistic classification in PyTorch/TensorFlow/scikit-learn with Fenchel-Young losses
  ☆192Updated 2 years ago
• ispamm / kernel-activation-functions
  Several implementations of the kernel-based activation functions
  ☆63Updated 6 years ago
• hughsalimbeni / DGPs_with_IWVI
  Deep Gaussian Processes with Importance-Weighted Variational Inference
  ☆39Updated 6 years ago
• brain-research / conv-sv
  The Singular Values of Convolutional Layers
  ☆72Updated 7 years ago
• golkar / backdrop
  Implementation and demonstration of backdrop in pytorch. Code and demonstration of GP dataset generator.
  ☆68Updated 7 years ago