talwagner / efficient_kdeLinks
Efficient LSH-based kernel density estimation
☆29Updated 5 years ago
Alternatives and similar repositories for efficient_kde
Users that are interested in efficient_kde are comparing it to the libraries listed below
Sorting:
- Source code for the ICML2019 paper "Subspace Robust Wasserstein Distances"☆29Updated 6 years ago
- Learning Generative Models across Incomparable Spaces (ICML 2019)☆27Updated 5 years ago
- Coresets☆37Updated 3 years ago
- Code for Sliced Gromov-Wasserstein☆69Updated 5 years ago
- Implementation of Graph Neural Tangent Kernel (NeurIPS 2019)☆105Updated 5 years ago
- Keras implementation of Deep Wasserstein Embeddings☆48Updated 7 years ago
- python implementation of Sinkhorn-Knopp☆33Updated 7 years ago
- The implementation code for our paper Wasserstein Embedding for Graph Learning (ICLR 2021).☆35Updated 4 years ago
- Python implementation of smooth optimal transport.☆60Updated 4 years ago
- Non-Parametric Calibration for Classification (AISTATS 2020)☆19Updated 3 years ago
- Gabriel Peyré, Marco Cuturi, Justin Solomon, Gromov-Wasserstein Averaging of Kernel and Distance Matrices, Proc. of ICML 2016.☆74Updated 9 years ago
- Stochastic algorithms for computing Regularized Optimal Transport☆58Updated 7 years ago
- [ICML 2020] Differentiating through the Fréchet Mean (https://arxiv.org/abs/2003.00335).☆56Updated 3 years ago
- a python implementation of various versions of the information bottleneck, including automated parameter searching☆128Updated 5 years ago
- PyTorch re-implementation of parts of "Deep Sets" (NIPS 2017)☆72Updated 7 years ago
- Implementation of the Sliced Wasserstein Autoencoder using PyTorch☆103Updated 6 years ago
- Implementation of the Gromov-Wasserstein distance to the setting of Unbalanced Optimal Transport☆45Updated 2 years ago
- 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
- Wasserstein regularization for sparse multi-task regression☆15Updated 5 years ago
- A Python implementation of Monge optimal transportation☆49Updated last year
- MMD, Hausdorff and Sinkhorn divergences scaled up to 1,000,000 samples.☆56Updated 6 years ago
- Implementation of the Neural Clustering Process algorithm in Pytorch☆31Updated 5 years ago
- Explaining a black-box using Deep Variational Information Bottleneck Approach☆46Updated 2 years ago
- NeurIPS 2022: Tree Mover’s Distance: Bridging Graph Metrics and Stability of Graph Neural Networks☆37Updated 2 years ago
- Code for our ICML '19 paper: Neural Network Attributions: A Causal Perspective.☆51Updated 3 years ago
- Code for "Generative causal explanations of black-box classifiers"☆35Updated 4 years ago
- Python implementation of Robust Continuous Clustering☆106Updated 6 years ago
- Self-Explaining Neural Networks☆13Updated 2 years ago
- Code for the paper 'Understanding Measures of Uncertainty for Adversarial Example Detection'☆61Updated 7 years ago
- Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors☆62Updated 5 years ago