talwagner / efficient_kde
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
- [NeurIPS 2019 Spotlight] High dimensional mean estimation and outlier detection in nearly-linear time.☆26Updated 5 years ago
- The implementation code for our paper Wasserstein Embedding for Graph Learning (ICLR 2021).☆33Updated 4 years ago
- Gromov-Wasserstein Learning for Graph Matching and Node Embedding☆72Updated 5 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
- Coresets☆37Updated 2 years ago
- Source code for the ICML2019 paper "Subspace Robust Wasserstein Distances"☆28Updated 5 years ago
- Learning Generative Models across Incomparable Spaces (ICML 2019)☆27Updated 5 years ago
- fast kernel evaluation in high dimensions via hashing☆23Updated 4 years ago
- Gabriel Peyré, Marco Cuturi, Justin Solomon, Gromov-Wasserstein Averaging of Kernel and Distance Matrices, Proc. of ICML 2016.☆73Updated 8 years ago
- Code for Sliced Gromov-Wasserstein☆67Updated 5 years ago
- MMD, Hausdorff and Sinkhorn divergences scaled up to 1,000,000 samples.☆55Updated 5 years ago
- MATLAB implementation of linear support vector classification in hyperbolic space☆20Updated 6 years ago
- This repository is the implementation of Deep Dirichlet Process Mixture Models (UAI 2022)☆13Updated 2 years ago
- Implementation of the Neural Clustering Process algorithm in Pytorch☆31Updated 4 years ago
- Python implementation of smooth optimal transport.☆57Updated 3 years ago
- Implementation of the Gromov-Wasserstein distance to the setting of Unbalanced Optimal Transport☆44Updated 2 years ago
- This is the source code for Learning Deep Kernels for Non-Parametric Two-Sample Tests (ICML2020).☆48Updated 3 years ago
- [ICML 2020] Differentiating through the Fréchet Mean (https://arxiv.org/abs/2003.00335).☆55Updated 3 years ago
- Implementation of the Multiscale Laplacian Graph Kernel☆18Updated 5 years ago
- NeurIPS 2022: Tree Mover’s Distance: Bridging Graph Metrics and Stability of Graph Neural Networks☆36Updated last year
- Python implementation of Robust Continuous Clustering☆104Updated 5 years ago
- Keras implementation of Deep Wasserstein Embeddings☆48Updated 6 years ago
- CO-Optimal Transport☆42Updated 4 years ago
- Explaining a black-box using Deep Variational Information Bottleneck Approach☆46Updated 2 years ago
- Implementation of Graph Neural Tangent Kernel (NeurIPS 2019)☆103Updated 5 years ago
- Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors☆62Updated 4 years ago
- Spatio-temporal alignements: Optimal transport in space and time☆43Updated 3 years ago
- Black Box Variational Inference for Bayesian logistic regression☆19Updated 7 years ago
- Implementation of the certificates proposed in the paper "Efficient Robustness Certificates for Discrete Data: Sparsity-Aware Randomized …☆35Updated last year