zalanborsos / coresets

Related projects: ⓘ

• francoispierrepaty / SubspaceRobustWasserstein
  Source code for the ICML2019 paper "Subspace Robust Wasserstein Distances"
  ☆27Updated 5 years ago
• IBM / wasserstein-barycenters
  Code for our ICLR19 paper "Wasserstein Barycenters for Model Ensembling", Pierre Dognin, Igor Melnyk, Youssef Mroueh, Jarret Ross, Cicero…
  ☆20Updated 4 years ago
• talwagner / efficient_kde
  Efficient LSH-based kernel density estimation
  ☆28Updated 4 years ago
• dtak / ocbnn-public
  General purpose library for BNNs, and implementation of OC-BNNs in our 2020 NeurIPS paper.
  ☆38Updated 2 years ago
• iamalexkorotin / Wasserstein2Barycenters
  PyTorch implementation of the paper "Continuous Wasserstein-2 Barycenter Estimation without Minimax Optimization" (ICLR 2021)
  ☆21Updated 2 years ago
• bunnech / gwgan
  Learning Generative Models across Incomparable Spaces (ICML 2019)
  ☆26Updated 4 years ago
• fengliu90 / DK-for-TST
  This is the source code for Learning Deep Kernels for Non-Parametric Two-Sample Tests (ICML2020).
  ☆46Updated 3 years ago
• mblondel / smooth-ot
  Python implementation of smooth optimal transport.
  ☆55Updated 3 years ago
• GiulsLu / Sinkhorn-Barycenters
  Sinkhorn Barycenters via Frank-Wolfe algorithm
  ☆24Updated 4 years ago
• ChongYou / robust-image-recovery
  ☆15Updated 3 years ago
• csinva / mdl-complexity
  MDL Complexity computations and experiments from the paper "Revisiting complexity and the bias-variance tradeoff".
  ☆17Updated last year
• kimiandj / gsw
  ☆39Updated 4 years ago
• naiqili / DDPM
  This repository is the implementation of Deep Dirichlet Process Mixture Models (UAI 2022)
  ☆12Updated 2 years ago
• Jiacheng-Zhu-AIML / WGPOT
  The Wasserstein Distance and Optimal Transport Map of Gaussian Processes
  ☆46Updated 4 years ago
• TongtongFANG / DIW
  Code for the paper "Rethinking Importance Weighting for Deep Learning under Distribution Shift".
  ☆24Updated 3 years ago
• bobby-he / bayesian-ntk
  Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'
  ☆26Updated 3 years ago
• JonathanWenger / pycalib
  Non-Parametric Calibration for Classification (AISTATS 2020)
  ☆18Updated 2 years ago
• mrojascarulla / causal_transfer_learning
  ☆30Updated 6 years ago
• fairkmeans / Fair-K-Means-Clustering
  Code of the paper Fair k-Means Clustering
  ☆13Updated 2 years ago
• twistedcubic / que-outlier-detection
  [NeurIPS 2019 Spotlight] High dimensional mean estimation and outlier detection in nearly-linear time.
  ☆26Updated 4 years ago
• aangelopoulos / private_prediction_sets
  Wrap around any model to output differentially private prediction sets with finite sample validity on any dataset.
  ☆17Updated 6 months ago
• mzalaya / screenkhorn
  Code for NeurIPS 2019 paper "Screening Sinkhorn Algorithm for Regularized Optimal Transport"
  ☆10Updated 4 years ago
• JasonAltschuler / OptimalTransportNIPS17
  Code for NIPS 2017 spotlight paper: "Near-linear time approximation algorithms for optimal transport via Sinkhorn iteration" by Jason Alt…
  ☆30Updated 6 years ago
• matthklein / fair_k_center_clustering
  Code for our paper "Fair k-Center Clustering for Data Summarization"
  ☆11Updated 5 years ago
• mfederici / dsit
  Implementation of the models and datasets used in "An Information-theoretic Approach to Distribution Shifts"
  ☆24Updated 2 years ago
• hichamjanati / debiased-ot-barycenters
  ☆23Updated 3 years ago
• RuntianZ / doro
  Distributional and Outlier Robust Optimization (ICML 2021)
  ☆27Updated 3 years ago
• audeg / Sinkhorn-GAN
  Learning generative models with Sinkhorn Loss
  ☆28Updated 5 years ago
• yaohungt / Pointwise_Dependency_Neural_Estimation
  ☆19Updated 4 years ago
• naiqili / DGPG
  Code for paper Stochastic Deep Gaussian Processes over Graphs
  ☆21Updated 2 years ago