BorisMuzellec / MissingDataOTLinks
A Pytorch implementation of missing data imputation using optimal transport.
☆103Updated 4 years ago
Alternatives and similar repositories for MissingDataOT
Users that are interested in MissingDataOT are comparing it to the libraries listed below
Sorting:
- The implementation code for our paper Wasserstein Embedding for Graph Learning (ICLR 2021).☆35Updated 4 years ago
- VAEs and nonlinear ICA: a unifying framework☆48Updated 6 years ago
- Implementation of the MIWAE method for deep generative modelling of incomplete data sets.☆41Updated last year
- Linxiao Yang, Ngai-Man Cheung, Jiaying Li, and Jun Fang, "Deep Clustering by Gaussian Mixture Variational Autoencoders with Graph Embeddi…☆52Updated 5 years ago
- Code for `BCD Nets: Scalable Variational Approaches for Bayesian Causal Discovery`, Neurips 2021☆26Updated 3 years ago
- Monte Carlo Flow Models for Data Imputation☆19Updated 5 years ago
- VAEs and nonlinear ICA: a unifying framework☆38Updated 5 years ago
- Disentangled gEnerative cAusal Representation (DEAR)☆62Updated 2 years ago
- Implementation of the Gromov-Wasserstein distance to the setting of Unbalanced Optimal Transport☆45Updated 2 years ago
- Code for Optimal Transport for structured data with application on graphs☆102Updated 2 years ago
- Python code of Hilbert-Schmidt Independence Criterion☆88Updated 3 years ago
- ☆119Updated 3 years ago
- ☆91Updated 2 years ago
- Diffusion Models for Causal Discovery☆86Updated 2 years ago
- Code for ICE-BeeM paper - NeurIPS 2020☆87Updated 4 years ago
- Learning Autoencoders with Relational Regularization☆46Updated 5 years ago
- ☆51Updated 9 months ago
- Uncertainty Aware Semi-Supervised Learning on Graph Data☆38Updated 4 years ago
- LEAP is a tool for discovering latent temporal causal relations with gradient-based neural network.☆37Updated 3 years ago
- A PyTorch Implementation of VaDE(https://arxiv.org/pdf/1611.05148.pdf)☆39Updated 4 years ago
- Classifier based mutual information, conditional mutual information estimation; conditional independence testing☆34Updated 6 years ago
- Code for Sliced Gromov-Wasserstein☆69Updated 5 years ago
- Contrastive Variational Autoencoders☆69Updated 6 years ago
- the reproduce of Variational Deep Embedding : A Generative Approach to Clustering Requirements by pytorch☆137Updated 2 years ago
- This repository holds the code for the paper "Deep Conditional Gaussian Mixture Model forConstrained Clustering".☆34Updated 3 years ago
- Official code for the ICLR 2021 paper Neural ODE Processes☆75Updated 3 years ago
- ☆96Updated 2 years ago
- TensorFlow implementation for the GP-VAE model described in https://arxiv.org/abs/1907.04155☆142Updated 2 years ago
- Python/R library for feature selection in neural nets. ("Feature selection using Stochastic Gates", ICML 2020)☆108Updated 3 years ago
- Efficient Conditionally Invariant Representation Learning (ICLR 2023, Oral)☆21Updated 2 years ago