BorisMuzellec / MissingDataOT
A Pytorch implementation of missing data imputation using optimal transport.
☆96Updated 3 years ago
Alternatives and similar repositories for MissingDataOT:
Users that are interested in MissingDataOT are comparing it to the libraries listed below
- Implementation of the MIWAE method for deep generative modelling of incomplete data sets.☆37Updated last year
- Code for the paper "Disentanglement by Nonlinear ICA with General Incompressible-flow Networks (GIN)" (2020)☆32Updated 3 years ago
- Official code for the ICLR 2021 paper Neural ODE Processes☆72Updated 2 years ago
- ☆90Updated last year
- VAEs and nonlinear ICA: a unifying framework☆47Updated 5 years ago
- Linxiao Yang, Ngai-Man Cheung, Jiaying Li, and Jun Fang, "Deep Clustering by Gaussian Mixture Variational Autoencoders with Graph Embeddi…☆52Updated 4 years ago
- Official PyTorch implementation of 🏁 MFCVAE 🏁: "Multi-Facet Clustering Variatonal Autoencoders (MFCVAE)" (NeurIPS 2021). A class of var…☆41Updated last year
- Classifier based mutual information, conditional mutual information estimation; conditional independence testing☆34Updated 5 years ago
- Learning Autoencoders with Relational Regularization☆46Updated 4 years ago
- LEAP is a tool for discovering latent temporal causal relations with gradient-based neural network.☆35Updated 2 years ago
- This repository holds the code for the paper "Deep Conditional Gaussian Mixture Model forConstrained Clustering".☆33Updated 3 years ago
- Implementation of the Gromov-Wasserstein distance to the setting of Unbalanced Optimal Transport☆44Updated 2 years ago
- Code for `BCD Nets: Scalable Variational Approaches for Bayesian Causal Discovery`, Neurips 2021☆25Updated 3 years ago
- Code for ICE-BeeM paper - NeurIPS 2020☆86Updated 3 years ago
- An encoder-decoder framework for learning from incomplete data☆46Updated last year
- Disentangled gEnerative cAusal Representation (DEAR)☆59Updated 2 years ago
- VAEs and nonlinear ICA: a unifying framework☆34Updated 4 years ago
- PyTorch implementation of "MIDA: Multiple Imputation using Denoising Autoencoders"☆28Updated 6 years ago
- The implementation code for our paper Wasserstein Embedding for Graph Learning (ICLR 2021).☆33Updated 4 years ago
- TensorFlow implementation for the GP-VAE model described in https://arxiv.org/abs/1907.04155☆135Updated last year
- Learning Generative Models across Incomparable Spaces (ICML 2019)☆27Updated 5 years ago
- A code for the NeurIPS 2022 Table Representation Learning Workshop paper: "Diffusion models for missing value imputation in tabular data"☆47Updated 9 months ago
- Tensorflow implementation for the SVGP-VAE model.☆22Updated 3 years ago
- ☆19Updated 4 years ago
- Code for Sliced Gromov-Wasserstein☆67Updated 5 years ago
- A PyTorch Implementation of VaDE(https://arxiv.org/pdf/1611.05148.pdf)☆36Updated 4 years ago
- Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.☆58Updated 4 years ago
- Implementation of the paper "Shapley Explanation Networks"☆88Updated 4 years ago
- DynGFN: Bayesian Dynamic Causal Discovery using Generative Flow Networks☆51Updated last year
- A benchmark for distribution shift in tabular data☆50Updated 9 months ago