Alternatives and similar repositories for IPAM_Tutorial_2019

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

• skolouri / swae
  Implementation of the Sliced Wasserstein Autoencoders
  ☆91Updated 7 years ago
• HaberGroup / SemiImplicitDNNs
  Pytorch implementation of 'Semi-Implicit Methods for Deep Neural Networks'
  ☆25Updated 6 years ago
• conormdurkan / autoregressive-energy-machines
  Autoregressive Energy Machines
  ☆78Updated 3 years ago
• duvenaud / learn-discrete
  Graduate topics course on learning discrete latent structure.
  ☆67Updated 6 years ago
• CUAI / Neural-Manifold-Ordinary-Differential-Equations
  [NeurIPS 2020] Neural Manifold Ordinary Differential Equations (https://arxiv.org/abs/2006.10254)
  ☆124Updated 2 years ago
• thegregyang / NNspectra
  Computing the eigenvalues of Neural Tangent Kernel and Conjugate Kernel (aka NNGP kernel) over the boolean cube
  ☆47Updated 6 years ago
• henripal / sgld
  ☆59Updated 6 years ago
• joeybose / HyperbolicNF
  ICML 2020 Paper: Latent Variable Modelling with Hyperbolic Normalizing Flows
  ☆54Updated 3 years ago
• pomonam / NoisyNaturalGradient
  TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".
  ☆60Updated 6 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
• 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
• jeanfeydy / global-divergences
  MMD, Hausdorff and Sinkhorn divergences scaled up to 1,000,000 samples.
  ☆57Updated 6 years ago
• CalculatedContent / ImplicitSelfRegularization
  Repo to accompany paper "Implicit Self-Regularization in Deep Neural Networks..."
  ☆47Updated 6 years ago
• rajatvd / NeuralODE
  Experiments with Neural ODEs and Adversarial Attacks
  ☆44Updated 6 years ago
• rflamary / OTML_Statlearn2018
  Courses and practical sessions for the Optimal Transport and Machine learning course at Statlearn 2018
  ☆26Updated 7 years ago
• mducoffe / Learning-Wasserstein-Embeddings
  Keras implementation of Deep Wasserstein Embeddings
  ☆48Updated 7 years ago
• AlliedToasters / synapses
  ☆71Updated 5 years ago
• PrincetonLIPS / reversible-inductive-construction
  Discrete Object Generation with Reversible Inductive Construction (NeurIPS 2019)
  ☆30Updated 4 years ago
• AdamCobb / LCBNN
  ☆25Updated 3 years ago
• ispamm / kernel-activation-functions
  Several implementations of the kernel-based activation functions
  ☆63Updated 6 years ago
• kekeblom / DeepCGP
  Deep convolutional gaussian processes.
  ☆82Updated 6 years ago
• lixilinx / psgd_tf
  Tensorflow implementation of preconditioned stochastic gradient descent
  ☆34Updated 2 years ago
• convnets-as-gps / convnets-as-gps
  Code for "Deep Convolutional Networks as shallow Gaussian Processes"
  ☆16Updated 6 years ago
• g-benton / learning-invariances
  Codebase for Learning Invariances in Neural Networks
  ☆96Updated 3 years ago
• ParthaEth / Regularized_autoencoders-RAE-
  ☆125Updated 2 years ago
• cambridge-mlg / cnn-gp
  Pytorch version of "Deep Convolutional Networks as shallow Gaussian Processes" by Adrià Garriga-Alonso, Carl Rasmussen and Laurence Aitch…
  ☆32Updated 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
• ColinQiyangLi / LConvNet
  Implementation of Methods Proposed in Preventing Gradient Attenuation in Lipschitz Constrained Convolutional Networks (NeurIPS 2019)
  ☆36Updated 5 years ago
• yassersouri / pytorch-deep-sets
  PyTorch re-implementation of parts of "Deep Sets" (NIPS 2017)
  ☆73Updated 7 years ago