Alternatives and similar repositories for H-Divergence

Users that are interested in H-Divergence are comparing it to the libraries listed below

• cunningham-lab / igr
  ☆30Updated 4 years ago
• wgrathwohl / LSD
  Official Release of "Learning the Stein Discrepancy for Training and Evaluating Energy-Based Models without Sampling"
  ☆49Updated 4 years ago
• yilundu / ebm_compositionality
  [NeurIPS'20] Code for the Paper Compositional Visual Generation and Inference with Energy Based Models
  ☆45Updated 2 years ago
• bobby-he / bayesian-ntk
  Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'
  ☆26Updated 4 years ago
• yaohungt / Pointwise_Dependency_Neural_Estimation
  ☆20Updated 4 years ago
• MichaelArbel / GeneralizedEBM
  ☆53Updated 10 months ago
• facebookresearch / InvarianceUnitTests
  Toy datasets to evaluate algorithms for domain generalization and invariance learning.
  ☆42Updated 3 years ago
• izmailovpavel / bnn_covariate_shift
  Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"
  ☆33Updated 2 years ago
• mingzhang-yin / ARM-gradient
  Low-variance, efficient and unbiased gradient estimation for optimizing models with binary latent variables. (ICLR 2019)
  ☆28Updated 6 years ago
• microsoft / conservative-uncertainty-estimation-random-priors
  Source code for paper Conservative Uncertainty Estimation By Fitting Prior Networks (ICLR 2020)
  ☆21Updated 2 years ago
• RuntianZ / doro
  Distributional and Outlier Robust Optimization (ICML 2021)
  ☆27Updated 3 years ago
• capybaralet / REx_code_release
  ☆63Updated 4 years ago
• kevin-w-li / deep-kexpfam
  ☆28Updated 3 years ago
• facebookresearch / BalancingGroups
  Simple data balancing baselines for worst-group-accuracy benchmarks.
  ☆42Updated last year
• mfederici / dsit
  Implementation of the models and datasets used in "An Information-theoretic Approach to Distribution Shifts"
  ☆25Updated 3 years ago
• ryoungj / optdom
  [ICLR'22] Self-supervised learning optimally robust representations for domain shift.
  ☆24Updated 3 years ago
• wgrathwohl / VERA
  ☆64Updated last year
• fengliu90 / DK-for-TST
  This is the source code for Learning Deep Kernels for Non-Parametric Two-Sample Tests (ICML2020).
  ☆49Updated 3 years ago
• team-approx-bayes / fromp
  Contains code for the NeurIPS 2020 paper by Pan et al., "Continual Deep Learning by FunctionalRegularisation of Memorable Past"
  ☆44Updated 4 years ago
• Faruk-Ahmed / predictive_group_invariance
  ☆34Updated 4 years ago
• AllanYangZhou / metalearning-symmetries
  Experiments for Meta-Learning Symmetries by Reparameterization
  ☆56Updated 4 years ago
• Sanaelotfi / Bayesian_model_comparison
  Supporing code for the paper "Bayesian Model Selection, the Marginal Likelihood, and Generalization".
  ☆35Updated 2 years ago
• ARM-gradient / ARSM
  Low-variance and unbiased gradient for backpropagation through categorical random variables, with application in variational auto-encoder…
  ☆17Updated 4 years ago
• jshe / wasserstein-2
  ☆13Updated 6 years ago
• bneyshabur / generalization-bounds
  Computing various measures and generalization bounds on convolutional and fully connected networks
  ☆35Updated 6 years ago
• AMLab-Amsterdam / FNP
  Implementation of the Functional Neural Process models
  ☆43Updated 4 years ago
• bethgelab / InDomainGeneralizationBenchmark
  ☆34Updated 3 years ago
• bpucla / latent-space-EBM-prior
  ☆36Updated 4 years ago
• JonathanWenger / pycalib
  Non-Parametric Calibration for Classification (AISTATS 2020)
  ☆19Updated 3 years ago
• henrygouk / mars-finetuning
  ☆19Updated 4 years ago