Alternatives and similar repositories for SIC

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

• bneyshabur / over-parametrization
  Computing various norms/measures on over-parametrized neural networks
  ☆50Updated 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 7 years ago
• facebookresearch / InvarianceUnitTests
  Toy datasets to evaluate algorithms for domain generalization and invariance learning.
  ☆43Updated 4 years ago
• zzzace2000 / FIDO-saliency
  Explaining Image Classifiers by Counterfactual Generation
  ☆28Updated 3 years ago
• wiseodd / natural-gradients
  Collection of algorithms for approximating Fisher Information Matrix for Natural Gradient (and second order method in general)
  ☆142Updated 6 years ago
• revbucket / geometric-certificates
  Geometric Certifications of Neural Nets
  ☆42Updated 3 years ago
• djsutherland / igms
  Implicit generative models and related stuff based on the MMD, in PyTorch
  ☆16Updated 5 years ago
• plai-group / tvo
  Code for the Thermodynamic Variational Objective
  ☆26Updated 3 years ago
• BeenKim / MMD-critic
  ☆135Updated 6 years ago
• conormdurkan / neural-statistician
  PyTorch Implementation of Neural Statistician
  ☆61Updated 3 years ago
• ruqizhang / csgmcmc
  Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning
  ☆93Updated 5 years ago
• ganguli-lab / deepchaos
  Experiments for the paper "Exponential expressivity in deep neural networks through transient chaos"
  ☆74Updated 9 years ago
• reiinakano / invariant-risk-minimization
  Implementation of Invariant Risk Minimization https://arxiv.org/abs/1907.02893
  ☆91Updated 5 years ago
• dtak / rrr
  Code/figures in Right for the Right Reasons
  ☆57Updated 5 years ago
• gd-zhang / noisy-K-FAC
  Natural Gradient, Variational Inference
  ☆29Updated 6 years ago
• wittawatj / interpretable-test
  NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.
  ☆64Updated 7 years ago
• AMLab-Amsterdam / MNF_VBNN
  Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks
  ☆65Updated 5 years ago
• ermongroup / BiasAndGeneralization
  ☆28Updated 6 years ago
• mmrl / disent-and-gen
  Code from the article: "The Role of Disentanglement in Generalisation" (ICLR, 2021).
  ☆21Updated 3 years ago
• modestyachts / neural_kernels_code
  ☆35Updated 4 years ago
• CalculatedContent / ImplicitSelfRegularization
  Repo to accompany paper "Implicit Self-Regularization in Deep Neural Networks..."
  ☆47Updated 7 years ago
• MichaelArbel / Scaled-MMD-GAN
  Scaled MMD GAN
  ☆36Updated 6 years ago
• ruosongwang / CNTK
  Convolutional Neural Tangent Kernel
  ☆112Updated 6 years ago
• MichaelArbel / GeneralizedEBM
  ☆54Updated last year
• pomonam / NoisyNaturalGradient
  TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".
  ☆60Updated 7 years ago
• joelouismarino / iterative_inference
  Implementation of iterative inference in deep latent variable models
  ☆43Updated 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
• SeojinBang / VIBI
  Explaining a black-box using Deep Variational Information Bottleneck Approach
  ☆46Updated 3 years ago
• csinva / hierarchical-dnn-interpretations
  Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)
  ☆129Updated 4 years ago
• emtiyaz / vmp-for-svae
  Variational Message Passing for Structured VAE (Code for ICLR 2018 paper)
  ☆47Updated 7 years ago