Alternatives and similar repositories for efficient_kde:

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

• francoispierrepaty / SubspaceRobustWasserstein
  Source code for the ICML2019 paper "Subspace Robust Wasserstein Distances"
  ☆28Updated 5 years ago
• twistedcubic / que-outlier-detection
  [NeurIPS 2019 Spotlight] High dimensional mean estimation and outlier detection in nearly-linear time.
  ☆26Updated 5 years ago
• zalanborsos / coresets
  Coresets
  ☆37Updated 3 years ago
• gpeyre / 2016-ICML-gromov-wasserstein
  Gabriel Peyré, Marco Cuturi, Justin Solomon, Gromov-Wasserstein Averaging of Kernel and Distance Matrices, Proc. of ICML 2016.
  ☆73Updated 8 years ago
• mblondel / smooth-ot
  Python implementation of smooth optimal transport.
  ☆58Updated 4 years ago
• kexinrong / rehashing
  fast kernel evaluation in high dimensions via hashing
  ☆23Updated 4 years ago
• mducoffe / Learning-Wasserstein-Embeddings
  Keras implementation of Deep Wasserstein Embeddings
  ☆48Updated 7 years ago
• lttam / TreeWasserstein
  Matlab code for tree-Wasserstein distance in the paper "Tree-Sliced Variants of Wasserstein Distances", NeurIPS, 2019. (Tam Le, Makoto Y…
  ☆11Updated 5 years ago
• tvayer / SGW
  Code for Sliced Gromov-Wasserstein
  ☆68Updated 5 years ago
• csinva / mdl-complexity
  MDL Complexity computations and experiments from the paper "Revisiting complexity and the bias-variance tradeoff".
  ☆18Updated last year
• antoninschrab / mmdagg-paper
  Reproducibility code for MMD Aggregated Two-Sample Test, by Schrab, Kim, Albert, Laurent, Guedj and Gretton: https://arxiv.org/abs/2110.1…
  ☆16Updated 11 months ago
• bunnech / gwgan
  Learning Generative Models across Incomparable Spaces (ICML 2019)
  ☆27Updated 5 years ago
• EigenPro / EigenPro2
  EigenPro2 iteration in Tensorflow (Keras)
  ☆23Updated 6 years ago
• hhcho / hyplinear
  MATLAB implementation of linear support vector classification in hyperbolic space
  ☆20Updated 6 years ago
• dmelis / SENN
  Self-Explaining Neural Networks
  ☆13Updated last year
• navid-naderi / WEGL
  The implementation code for our paper Wasserstein Embedding for Graph Learning (ICLR 2021).
  ☆35Updated 4 years ago
• dmilios / dirichletGPC
  ☆17Updated 6 years ago
• wittawatj / interpretable-test
  NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.
  ☆63Updated 6 years ago
• arthurmensch / online_sinkhorn
  ☆13Updated 4 years ago
• jeanfeydy / global-divergences
  MMD, Hausdorff and Sinkhorn divergences scaled up to 1,000,000 samples.
  ☆55Updated 6 years ago
• brain-research / ncp
  Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors
  ☆62Updated 5 years ago
• skolouri / swae
  Implementation of the Sliced Wasserstein Autoencoders
  ☆91Updated 6 years ago
• btaba / sinkhorn_knopp
  python implementation of Sinkhorn-Knopp
  ☆33Updated 7 years ago
• KangchengHou / gntk
  Implementation of Graph Neural Tangent Kernel (NeurIPS 2019)
  ☆104Updated 5 years ago
• ucla-vision / information-dropout
  Implementation of Information Dropout
  ☆39Updated 7 years ago
• CUAI / Differentiable-Frechet-Mean
  [ICML 2020] Differentiating through the Fréchet Mean (https://arxiv.org/abs/2003.00335).
  ☆55Updated 3 years ago
• lzzcd001 / ade-code
  Code for "Exponential Family Estimation via Adversarial Dynamics Embedding" (NeurIPS 2019)
  ☆13Updated 5 years ago
• ColinQiyangLi / LConvNet
  Implementation of Methods Proposed in Preventing Gradient Attenuation in Lipschitz Constrained Convolutional Networks (NeurIPS 2019)
  ☆35Updated 4 years ago
• icml-mcbn / mcbn
  ☆53Updated 7 years ago
• kohpangwei / group-influence-release
  ☆50Updated 2 years ago