Alternatives and similar repositories for IPAM_Tutorial_2019

Users that are interested in IPAM_Tutorial_2019 are comparing it to the libraries listed below

• duvenaud / learn-discrete
  Graduate topics course on learning discrete latent structure.
  ☆67Updated 7 years ago
• HaberGroup / SemiImplicitDNNs
  Pytorch implementation of 'Semi-Implicit Methods for Deep Neural Networks'
  ☆25Updated 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
• CUAI / Neural-Manifold-Ordinary-Differential-Equations
  [NeurIPS 2020] Neural Manifold Ordinary Differential Equations (https://arxiv.org/abs/2006.10254)
  ☆125Updated 2 years ago
• conormdurkan / autoregressive-energy-machines
  Autoregressive Energy Machines
  ☆78Updated 3 years ago
• thegregyang / NNspectra
  Computing the eigenvalues of Neural Tangent Kernel and Conjugate Kernel (aka NNGP kernel) over the boolean cube
  ☆48Updated 6 years ago
• ritchieng / eigenvectors-from-eigenvalues
  PyTorch implementation comparison of old and new method of determining eigenvectors from eigenvalues.
  ☆98Updated 4 years ago
• PrincetonLIPS / reversible-inductive-construction
  Discrete Object Generation with Reversible Inductive Construction (NeurIPS 2019)
  ☆30Updated 4 years ago
• skolouri / swae
  Implementation of the Sliced Wasserstein Autoencoders
  ☆92Updated 7 years ago
• joeybose / HyperbolicNF
  ICML 2020 Paper: Latent Variable Modelling with Hyperbolic Normalizing Flows
  ☆54Updated 3 years ago
• kekeblom / DeepCGP
  Deep convolutional gaussian processes.
  ☆82Updated 6 years ago
• AdamCobb / LCBNN
  ☆25Updated 3 years ago
• lzzcd001 / ade-code
  Code for "Exponential Family Estimation via Adversarial Dynamics Embedding" (NeurIPS 2019)
  ☆14Updated 6 years ago
• yaohungt / Adaptive-Regularization-Neural-Network
  [NeurIPS'19] [PyTorch] Adaptive Regularization in NN
  ☆68Updated 6 years ago
• convnets-as-gps / convnets-as-gps
  Code for "Deep Convolutional Networks as shallow Gaussian Processes"
  ☆16Updated 6 years ago
• IraKorshunova / bruno
  a deep recurrent model for exchangeable data
  ☆34Updated 5 years ago
• ermongroup / higher_order_invariance
  Code for "Accelerating Natural Gradient with Higher-Order Invariance"
  ☆30Updated 6 years ago
• JeanKossaifi / caltech-tutorial
  Material for my Caltech tutorial on deep learning and tensor methods
  ☆70Updated 7 years ago
• brain-research / ncp
  Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors
  ☆62Updated 5 years ago
• Orcuslc / OrthNet
  TensorFlow, PyTorch and Numpy layers for generating Orthogonal Polynomials
  ☆31Updated 7 years ago
• lixilinx / psgd_tf
  Tensorflow implementation of preconditioned stochastic gradient descent
  ☆34Updated 2 years ago
• YingzhenLi / SteinGrad
  Code release for the ICLR paper
  ☆21Updated 7 years ago
• lxuechen / BDMC
  PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.
  ☆52Updated 4 years ago
• ispamm / kernel-activation-functions
  Several implementations of the kernel-based activation functions
  ☆63Updated 6 years ago
• yassersouri / pytorch-deep-sets
  PyTorch re-implementation of parts of "Deep Sets" (NIPS 2017)
  ☆73Updated 7 years ago
• SebFar / radial_bnn
  Code to accompany the paper Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep Learning
  ☆33Updated 5 years ago
• brain-research / conv-sv
  The Singular Values of Convolutional Layers
  ☆72Updated 7 years ago
• zlin7 / CGNet
  ☆70Updated 2 years ago
• KarenUllrich / binary-VAE
  A minimal implementation of a VAE with BinConcrete (relaxed Bernoulli) latent distribution in TensorFlow.
  ☆22Updated 6 years ago
• abdulfatir / normalizing-flows
  Understanding normalizing flows
  ☆132Updated 6 years ago