Alternatives and similar repositories for RotNIST

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

• AMLab-Amsterdam / FNP
  Implementation of the Functional Neural Process models
  ☆43Updated 5 years ago
• brain-research / ncp
  Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors
  ☆62Updated 5 years ago
• MichaelArbel / GeneralizedEBM
  ☆54Updated last year
• gbaydin / hypergradient-descent
  Hypergradient descent
  ☆149Updated last year
• fengliu90 / DK-for-TST
  This is the source code for Learning Deep Kernels for Non-Parametric Two-Sample Tests (ICML2020).
  ☆50Updated 4 years ago
• djstrouse / information-bottleneck
  a python implementation of various versions of the information bottleneck, including automated parameter searching
  ☆128Updated 5 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
• ucla-vision / information-dropout
  Implementation of Information Dropout
  ☆39Updated 8 years ago
• widedeepnetworks / widedeepnetworks
  Code for the paper Gaussian process behaviour in wide deep networks
  ☆46Updated 6 years ago
• alexalemi / vib_demo
  ☆91Updated 3 years ago
• mingzhang-yin / SIVI
  A variational inference method with accurate uncertainty estimation. It uses a new semi-implicit variational family built on neural netwo…
  ☆54Updated 9 months ago
• conormdurkan / neural-statistician
  PyTorch Implementation of Neural Statistician
  ☆60Updated 3 years ago
• AllanYangZhou / metalearning-symmetries
  Experiments for Meta-Learning Symmetries by Reparameterization
  ☆56Updated 4 years ago
• MichaelArbel / Scaled-MMD-GAN
  Scaled MMD GAN
  ☆36Updated 5 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
• dimkal89 / rvae
  ☆38Updated 5 years ago
• modestyachts / neural_kernels_code
  ☆36Updated 4 years ago
• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆48Updated 5 years ago
• microsoft / deterministic-variational-inference
  Sample code for running deterministic variational inference to train Bayesian neural networks
  ☆100Updated 6 years ago
• cunningham-lab / igr
  ☆30Updated 4 years ago
• YingzhenLi / SteinGrad
  Code release for the ICLR paper
  ☆21Updated 7 years ago
• Piyushi-0 / ACE
  Code for our ICML '19 paper: Neural Network Attributions: A Causal Perspective.
  ☆51Updated 3 years ago
• ucla-vision / entropy-sgd
  Lua implementation of Entropy-SGD
  ☆82Updated 7 years ago
• lsgos / uncertainty-adversarial-paper
  Code for the paper 'Understanding Measures of Uncertainty for Adversarial Example Detection'
  ☆61Updated 7 years ago
• revbucket / geometric-certificates
  Geometric Certifications of Neural Nets
  ☆42Updated 2 years ago
• eifuentes / swae-pytorch
  Implementation of the Sliced Wasserstein Autoencoder using PyTorch
  ☆103Updated 6 years ago
• iffsid / disentangling-disentanglement
  ☆91Updated 6 years ago
• locuslab / monotone_op_net
  Monotone operator equilibrium networks
  ☆53Updated 5 years ago
• ruqizhang / csgmcmc
  Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning
  ☆92Updated 4 years ago
• siplab-gt / VAELLS
  Code for "Variational Autoencoder with Learned Latent Structure"
  ☆34Updated 4 years ago