zalanborsos / coresetsLinks
Coresets
☆38Updated 3 years ago
Alternatives and similar repositories for coresets
Users that are interested in coresets are comparing it to the libraries listed below
Sorting:
- Source code for the ICML2019 paper "Subspace Robust Wasserstein Distances"☆29Updated 6 years ago
- Code for Sliced Gromov-Wasserstein☆69Updated 6 years ago
- Efficient LSH-based kernel density estimation☆28Updated 6 years ago
- Stochastic algorithms for computing Regularized Optimal Transport☆58Updated 7 years ago
- This is the source code for Learning Deep Kernels for Non-Parametric Two-Sample Tests (ICML2020).☆53Updated 4 years ago
- A Pytorch implementation of missing data imputation using optimal transport.☆105Updated 4 years ago
- Classifier based mutual information, conditional mutual information estimation; conditional independence testing☆35Updated 6 years ago
- Code for our ICLR19 paper "Wasserstein Barycenters for Model Ensembling", Pierre Dognin, Igor Melnyk, Youssef Mroueh, Jarret Ross, Cicero…☆23Updated 6 years ago
- General purpose library for BNNs, and implementation of OC-BNNs in our 2020 NeurIPS paper.☆39Updated 3 years ago
- Sliced Wasserstein Distance for Learning Gaussian Mixture Models☆66Updated 2 years ago
- Python implementation of smooth optimal transport.☆61Updated 4 years ago
- Sliced Wasserstein Generator☆22Updated 7 years ago
- Learning generative models with Sinkhorn Loss☆30Updated 7 years ago
- A Python implementation of Monge optimal transportation☆49Updated 2 years ago
- Code for the ICML 2021 paper "Bridging Multi-Task Learning and Meta-Learning: Towards Efficient Training and Effective Adaptation", Haoxi…☆68Updated 4 years ago
- Learning Generative Models across Incomparable Spaces (ICML 2019)☆27Updated 5 years ago
- ☆42Updated 5 years ago
- Explaining a black-box using Deep Variational Information Bottleneck Approach☆46Updated 3 years ago
- Implementation of the Neural Clustering Process algorithm in Pytorch☆32Updated 5 years ago
- Sinkhorn Barycenters via Frank-Wolfe algorithm☆27Updated 5 years ago
- Implementation of the Sliced Wasserstein Autoencoder using PyTorch☆101Updated 7 years ago
- PyTorch re-implementation of parts of "Deep Sets" (NIPS 2017)☆73Updated 7 years ago
- Code for "Learning with minibatch Wasserstein: asymptotic and gradient properties".☆13Updated 4 years ago
- Pytorch Implementation of the Nonlinear Information Bottleneck☆41Updated last year
- Implementation of the models and datasets used in "An Information-theoretic Approach to Distribution Shifts"☆25Updated 4 years ago
- Learning Autoencoders with Relational Regularization☆46Updated 5 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆83Updated last year
- Code of the paper Fair k-Means Clustering☆13Updated 4 years ago
- Code for NIPS 2017 spotlight paper: "Near-linear time approximation algorithms for optimal transport via Sinkhorn iteration" by Jason Alt…☆31Updated 8 years ago
- Keras implementation of Deep Wasserstein Embeddings☆48Updated 7 years ago