HongtengXu / Relational-AutoEncodersLinks
Learning Autoencoders with Relational Regularization
☆46Updated 4 years ago
Alternatives and similar repositories for Relational-AutoEncoders
Users that are interested in Relational-AutoEncoders are comparing it to the libraries listed below
Sorting:
- Contains the code relative to the paper Partial Gromov-Wasserstein with Applications on Positive-Unlabeled Learning https://arxiv.org/abs…☆21Updated 5 years ago
- Code for Sliced Gromov-Wasserstein☆68Updated 5 years ago
- Learning Generative Models across Incomparable Spaces (ICML 2019)☆27Updated 5 years ago
- Implementation of the Gromov-Wasserstein distance to the setting of Unbalanced Optimal Transport☆44Updated 2 years ago
- Stochastic algorithms for computing Regularized Optimal Transport☆57Updated 6 years ago
- Gromov-Wasserstein Factorization Models for Graph Clustering (AAAI-20)☆31Updated 2 years ago
- Gromov-Wasserstein Learning for Graph Matching and Node Embedding☆72Updated 5 years ago
- Code for Optimal Transport for structured data with application on graphs☆100Updated 2 years ago
- [ICML 2020] Differentiating through the Fréchet Mean (https://arxiv.org/abs/2003.00335).☆56Updated 3 years ago
- Implementation of the Sliced Wasserstein Autoencoder using PyTorch☆103Updated 6 years ago
- Code for "Learning with minibatch Wasserstein: asymptotic and gradient properties".☆13Updated 4 years ago
- Statistics on the space of asymmetric networks via Gromov-Wasserstein distance☆13Updated 5 years ago
- Code accompanying the NeurIPS 2019 paper "GOT: An Optimal Transport framework for Graph comparison"☆41Updated last year
- Mixed-curvature Variational Autoencoders (ICLR 2020)☆62Updated 4 years ago
- Source code for the ICML2019 paper "Subspace Robust Wasserstein Distances"☆28Updated 6 years ago
- A PyTorch Implementation of VaDE(https://arxiv.org/pdf/1611.05148.pdf)☆39Updated 4 years ago
- Anonymized code for ICLR 2019 submission "Understanding and Improving Interpolation in Autoencoders via an Adversarial Regularizer"☆20Updated 6 years ago
- A Pytorch implementation of the optimal transport kernel embedding☆117Updated 4 years ago
- Code for Neural Manifold Clustering and Embedding☆59Updated 3 years ago
- Code for the paper "Disentanglement by Nonlinear ICA with General Incompressible-flow Networks (GIN)" (2020)☆32Updated 3 years ago
- ☆68Updated 6 years ago
- HGCAE Pytorch implementation. CVPR2021 accepted.☆44Updated last year
- Gaussian Process Prior Variational Autoencoder☆84Updated 6 years ago
- Linxiao Yang, Ngai-Man Cheung, Jiaying Li, and Jun Fang, "Deep Clustering by Gaussian Mixture Variational Autoencoders with Graph Embeddi…☆53Updated 5 years ago
- Official Python3 implementation of our ICML 2021 paper "Unbalanced minibatch Optimal Transport; applications to Domain Adaptation"☆46Updated 2 years ago
- The implementation code for our paper Wasserstein Embedding for Graph Learning (ICLR 2021).☆35Updated 4 years ago
- ☆40Updated 5 years ago
- [ICML2023] InfoOT: Information Maximizing Optimal Transport☆41Updated 2 years ago
- Disentangled gEnerative cAusal Representation (DEAR)☆60Updated 2 years ago
- Implementation of "Learning latent subspaces in variational autoencoders"☆20Updated 5 years ago