Alternatives and similar repositories for coresets

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

• bobby-he / bayesian-ntk
  Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'
  ☆26Updated 4 years ago
• JonathanWenger / pycalib
  Non-Parametric Calibration for Classification (AISTATS 2020)
  ☆19Updated 3 years ago
• talwagner / efficient_kde
  Efficient LSH-based kernel density estimation
  ☆29Updated 5 years ago
• mfederici / dsit
  Implementation of the models and datasets used in "An Information-theoretic Approach to Distribution Shifts"
  ☆25Updated 3 years ago
• litian96 / TERM
  Tilted Empirical Risk Minimization (ICLR '21)
  ☆59Updated 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
• francoispierrepaty / SubspaceRobustWasserstein
  Source code for the ICML2019 paper "Subspace Robust Wasserstein Distances"
  ☆28Updated 5 years ago
• mblondel / smooth-ot
  Python implementation of smooth optimal transport.
  ☆58Updated 4 years ago
• Srceh / DistCal
  Code for the ICML 2019 paper: Distribution Calibration for Regression
  ☆21Updated last year
• cambridge-mlg / cnn-gp
  Pytorch version of "Deep Convolutional Networks as shallow Gaussian Processes" by Adrià Garriga-Alonso, Carl Rasmussen and Laurence Aitch…
  ☆32Updated 5 years ago
• gwgundersen / rflvm
  Random feature latent variable models in Python
  ☆22Updated last year
• twistedcubic / que-outlier-detection
  [NeurIPS 2019 Spotlight] High dimensional mean estimation and outlier detection in nearly-linear time.
  ☆26Updated 5 years ago
• mrojascarulla / causal_transfer_learning
  ☆32Updated 6 years ago
• IBM / wasserstein-barycenters
  Code for our ICLR19 paper "Wasserstein Barycenters for Model Ensembling", Pierre Dognin, Igor Melnyk, Youssef Mroueh, Jarret Ross, Cicero…
  ☆22Updated 5 years ago
• skolouri / swgmm
  Sliced Wasserstein Distance for Learning Gaussian Mixture Models
  ☆62Updated 2 years ago
• iamalexkorotin / Wasserstein2Barycenters
  PyTorch implementation of the paper "Continuous Wasserstein-2 Barycenter Estimation without Minimax Optimization" (ICLR 2021)
  ☆23Updated 2 years ago
• matthieuheitz / WassersteinDictionaryLearning
  Morgan A. Schmitz., Matthieu Heitz, Nicolas Bonneel, Fred Ngole, David Coeurjolly, Marco Cuturi, Gabriel Peyré, and Jean-Luc Starck. "Was…
  ☆19Updated 5 years ago
• navid-naderi / WEGL
  The implementation code for our paper Wasserstein Embedding for Graph Learning (ICLR 2021).
  ☆35Updated 4 years ago
• aripakman / neural_clustering_process
  Implementation of the Neural Clustering Process algorithm in Pytorch
  ☆31Updated 4 years ago
• bunnech / gwgan
  Learning Generative Models across Incomparable Spaces (ICML 2019)
  ☆27Updated 5 years ago
• diviyank / SAM
  Code for the Structural Agnostic Model (https://arxiv.org/abs/1803.04929)
  ☆52Updated 4 years ago
• BorgwardtLab / WTK
  A Wasserstein Subsequence Kernel for Time Series.
  ☆21Updated 11 months ago
• sudiptodip15 / CCMI
  Classifier based mutual information, conditional mutual information estimation; conditional independence testing
  ☆34Updated 5 years ago
• boschresearch / GMM_DAE
  ☆20Updated 3 years ago
• burklight / nonlinear-IB-PyTorch
  Pytorch Implementation of the Nonlinear Information Bottleneck
  ☆40Updated 10 months ago
• naiqili / DGPG
  Code for paper Stochastic Deep Gaussian Processes over Graphs
  ☆22Updated 3 years ago
• meyerscetbon / LOT
  ☆17Updated 2 years ago
• k9k2 / qSGD
  SGD and Ordered SGD codes for deep learning, SVM, and logistic regression
  ☆35Updated 4 years ago
• yaohungt / Pointwise_Dependency_Neural_Estimation
  ☆20Updated 4 years ago
• levelfour / SU_Classification
  Implementation for "Classification from Pairwise Similarity and Unlabeled Data"
  ☆27Updated 5 years ago