Alternatives and similar repositories for SemiImplicitDNNs

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

• pomonam / NoisyNaturalGradient
  TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".
  ☆60Updated 6 years ago
• toiaydcdyywlhzvlob / backpack
  This repository is no longer maintained. Check
  ☆81Updated 5 years ago
• robintibor / generative-reversible
  ☆32Updated 7 years ago
• convnets-as-gps / convnets-as-gps
  Code for "Deep Convolutional Networks as shallow Gaussian Processes"
  ☆16Updated 6 years ago
• brain-research / ncp
  Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors
  ☆62Updated 5 years ago
• ermongroup / mintnet
  MintNet: Building Invertible Neural Networks with Masked Convolutions
  ☆39Updated 4 years ago
• jrbtaylor / conditional-pixelcnn
  A PyTorch implementation of Conditional PixelCNNs
  ☆27Updated 7 years ago
• locuslab / monotone_op_net
  Monotone operator equilibrium networks
  ☆53Updated 5 years ago
• modestyachts / neural_kernels_code
  ☆36Updated 4 years ago
• SkafteNicki / libcpab
  CPAB Transformations: finite-dimensional spaces of simple, fast, and highly-expressive diffeomorphisms derived from parametric, continuou…
  ☆50Updated 4 years ago
• asteroidhouse / self-tuning-networks
  Code for Self-Tuning Networks (ICLR 2019) https://arxiv.org/abs/1903.03088
  ☆53Updated 6 years ago
• ehoogeboom / emerging
  ☆42Updated 6 years ago
• ebekkers / gsplinets
  B-Spline CNNs on Lie groups
  ☆54Updated 5 years ago
• kekeblom / DeepCGP
  Deep convolutional gaussian processes.
  ☆80Updated 5 years ago
• skolouri / swae
  Implementation of the Sliced Wasserstein Autoencoders
  ☆90Updated 7 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
• conormdurkan / autoregressive-energy-machines
  Autoregressive Energy Machines
  ☆78Updated 2 years ago
• cunningham-lab / igr
  ☆30Updated 4 years ago
• PrincetonLIPS / RandomizedAutomaticDifferentiation
  Experiment code for "Randomized Automatic Differentiation"
  ☆67Updated 5 years ago
• ColinQiyangLi / LConvNet
  Implementation of Methods Proposed in Preventing Gradient Attenuation in Lipschitz Constrained Convolutional Networks (NeurIPS 2019)
  ☆35Updated 5 years ago
• g-benton / learning-invariances
  Codebase for Learning Invariances in Neural Networks
  ☆95Updated 2 years ago
• ml-research / pau
  Padé Activation Units: End-to-end Learning of Activation Functions in Deep Neural Network
  ☆63Updated 4 years ago
• AlexanderMath / fasth
  Code for the article "What if Neural Networks had SVDs?", to be presented as a spotlight paper at NeurIPS 2020.
  ☆76Updated last year
• MinhyungCho / riemannian-batch-normalization-pytorch
  Riemannian approach to batch normalization
  ☆22Updated 7 years ago
• YingzhenLi / SteinGrad
  Code release for the ICLR paper
  ☆21Updated 7 years ago
• ermongroup / higher_order_invariance
  Code for "Accelerating Natural Gradient with Higher-Order Invariance"
  ☆30Updated 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
• xbresson / IPAM_Tutorial_2019
  Notebooks for IPAM Tutorial, March 15 2019
  ☆24Updated 6 years ago
• fKunstner / limitations-empirical-fisher
  Limitations of the Empirical Fisher Approximation
  ☆47Updated 5 months ago
• jeanfeydy / global-divergences
  MMD, Hausdorff and Sinkhorn divergences scaled up to 1,000,000 samples.
  ☆56Updated 6 years ago