Alternatives and similar repositories for AgnosticMeanAndCovarianceCode:

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

• hoonose / robust-filter
  [ICML 2017] Robust estimation of mean and covariance in high dimensions
  ☆34Updated 4 years ago
• GiulsLu / OT-gradients
  ☆12Updated 6 years ago
• aburnap / Mixed-Membership-Stochastic-Blockmodel
  Mixed Membership Stochastic Blockmodel Implementation with 3 Inference Schemes
  ☆24Updated 9 years ago
• keyonvafa / logistic-reg-bbvi-blog
  Black Box Variational Inference for Bayesian logistic regression
  ☆19Updated 7 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…
  ☆53Updated 3 months ago
• mauriziofilippone / deep_gp_random_features
  ☆40Updated 5 years ago
• namkoong-lab / robustopt
  ☆42Updated 6 years ago
• karlnapf / kernel_exp_family
  Various estimators of the infinite dimensional exponential family model
  ☆15Updated 7 years ago
• duchi-lab / certifiable-distributional-robustness
  Certifying Some Distributional Robustness with Principled Adversarial Training (https://arxiv.org/abs/1710.10571)
  ☆45Updated 6 years ago
• jmikko / fair_ERM
  Fair Empirical Risk Minimization (FERM)
  ☆37Updated 4 years ago
• markvdw / GPflow-inter-domain
  Gaussian processes in TensorFlow with modifications to allow inter-domain inducing variables
  ☆13Updated 7 years ago
• rajatsen91 / CCIT
  Classifier Conditional Independence Test: A CI test that uses a binary classifier (XGBoost) for CI testing
  ☆46Updated last year
• Networks-Learning / hdhp.py
  Code for "Hierarchical Dirichlet-Hawkes process: generative model and inference algorithm", WWW 2017
  ☆36Updated 6 years ago
• wittawatj / interpretable-test
  NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.
  ☆63Updated 6 years ago
• daeilkim / bbvi
  Black Box Variational Inference
  ☆14Updated 9 years ago
• thjashin / gp-infer-net
  Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019
  ☆41Updated 2 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
• YingzhenLi / vae_renyi_divergence
  A tensorflow implementation of VAE training with Renyi divergence
  ☆31Updated 8 years ago
• audeg / StochasticOT
  Stochastic Optimization for Optimal Transport
  ☆22Updated 8 years ago
• kasparmartens / NeuralProcesses
  Neural Processes implementation for 1D regression
  ☆65Updated 5 years ago
• blei-lab / ars-reparameterization
  Source code for Naesseth et. al. "Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms" (2017)
  ☆39Updated 7 years ago
• jamesmcinerney / vbmm
  Variational inference for Gaussian mixture models
  ☆34Updated 11 years ago
• hichamjanati / srf
  Random Fourier Features
  ☆50Updated 7 years ago
• YingzhenLi / VRbound
  code release for the NIPS 2016 paper
  ☆26Updated 8 years ago
• mijungi / dpem_code
  ☆8Updated 7 years ago
• fengliu90 / DK-for-TST
  This is the source code for Learning Deep Kernels for Non-Parametric Two-Sample Tests (ICML2020).
  ☆48Updated 3 years ago
• MFreidank / pysgmcmc
  Bayesian Deep Learning with Stochastic Gradient MCMC Methods
  ☆38Updated 3 years ago
• yujiali / gmmn
  Generative moment matching networks
  ☆149Updated 8 years ago
• ssydasheng / FBNN
  Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)
  ☆80Updated 4 years ago
• edoliberty / frequent-directions-experiments
  Contains matrix sketching algorithms in python
  ☆16Updated 2 years ago