Alternatives and similar repositories for AgnosticMeanAndCovarianceCode

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

• namkoong-lab / robustopt
  ☆43Updated 6 years ago
• rajatsen91 / CCIT
  Classifier Conditional Independence Test: A CI test that uses a binary classifier (XGBoost) for CI testing
  ☆45Updated last year
• mauriziofilippone / deep_gp_random_features
  ☆40Updated 6 years ago
• aburnap / Mixed-Membership-Stochastic-Blockmodel
  Mixed Membership Stochastic Blockmodel Implementation with 3 Inference Schemes
  ☆24Updated 9 years ago
• duchi-lab / certifiable-distributional-robustness
  Certifying Some Distributional Robustness with Principled Adversarial Training (https://arxiv.org/abs/1710.10571)
  ☆45Updated 7 years ago
• hoonose / robust-filter
  [ICML 2017] Robust estimation of mean and covariance in high dimensions
  ☆33Updated 4 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 8 months ago
• keyonvafa / logistic-reg-bbvi-blog
  Black Box Variational Inference for Bayesian logistic regression
  ☆18Updated 8 years ago
• thjashin / gp-infer-net
  Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019
  ☆41Updated 2 years ago
• alexalemi / vib_demo
  ☆91Updated 3 years ago
• MFreidank / pysgmcmc
  Bayesian Deep Learning with Stochastic Gradient MCMC Methods
  ☆39Updated 3 years ago
• LeoYu / neural-tangent-kernel-UCI
  Testing Nerual Tangent Kernel (NTK) on small UCI datasets
  ☆81Updated 5 years ago
• blei-lab / variational-smc
  Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)
  ☆65Updated 6 years ago
• fengliu90 / DK-for-TST
  This is the source code for Learning Deep Kernels for Non-Parametric Two-Sample Tests (ICML2020).
  ☆49Updated 4 years ago
• hichamjanati / srf
  Random Fourier Features
  ☆50Updated 8 years ago
• GiulsLu / OT-gradients
  ☆12Updated 6 years ago
• jmikko / fair_ERM
  Fair Empirical Risk Minimization (FERM)
  ☆37Updated 4 years ago
• DartML / Stein-Variational-Gradient-Descent
  code for the paper "Stein Variational Gradient Descent (SVGD): A General Purpose Bayesian Inference Algorithm"
  ☆101Updated 6 years ago
• YingzhenLi / vae_renyi_divergence
  A tensorflow implementation of VAE training with Renyi divergence
  ☆31Updated 8 years ago
• Networks-Learning / hdhp.py
  Code for "Hierarchical Dirichlet-Hawkes process: generative model and inference algorithm", WWW 2017
  ☆36Updated 6 years ago
• ytsmiling / lmt
  Public code for a paper "Lipschitz-Margin Training: Scalable Certification of Perturbation Invariance for Deep Neural Networks."
  ☆34Updated 6 years ago
• mstaib / stochastic-barycenter-code
  Supporting code for "Parallel Streaming Wasserstein Barycenters"
  ☆10Updated 7 years ago
• kasparmartens / NeuralProcesses
  Neural Processes implementation for 1D regression
  ☆65Updated 6 years ago
• umutsimsekli / sgd_tail_index
  The codebase for the paper "A Tail-Index Analysis of Stochastic Gradient Noise in Deep Neural Networks"
  ☆25Updated 5 years ago
• criteo-research / optimization-continuous-action-crm
  ☆30Updated 5 years ago
• otokonoko8 / implicit-variational-inference
  The collection of recent papers about variational inference
  ☆85Updated 5 years ago
• walidk / AcceleratedMirrorDescent
  ☆12Updated 9 years ago
• ssydasheng / FBNN
  Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)
  ☆85Updated 4 years ago
• wittawatj / interpretable-test
  NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.
  ☆63Updated 7 years ago
• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆48Updated 5 years ago