| Name | Version | Summary | date |
| pi-vae-pytorch |
1.0.0b3 |
A Pytorch implementation of Poisson Identifiable VAE (pi-VAE), a variational auto encoder used to construct latent variable models of neural activity while simultaneously modeling the relation between the latent and task variables. |
2024-04-03 02:43:21 |
| hvae-backbone |
0.1.126 |
Universal and customizable implementation of the Hierarchical Variational Autoencoder architecture. |
2024-02-05 12:19:53 |
| fusilli |
1.2.3 |
Comparing multi-modal data fusion methods. Don't be silly, use Fusilli! |
2024-02-01 12:27:40 |
| pg-sui |
1.0.2.1 |
Python machine and deep learning package to impute missing SNPs |
2023-09-12 06:44:05 |
| vae_anomaly_detection |
2.0.1 |
Pytorch/TF1 implementation of Variational AutoEncoder for anomaly detection following the paper "Variational Autoencoder based Anomaly Detection using Reconstruction Probability by Jinwon An, Sungzoon Cho" |
2023-08-28 19:41:39 |
| probaforms |
0.2.0 |
Synthetic data generation for tables. |
2023-07-26 18:15:04 |
| PG-SUI |
0.2 |
Python machine and deep learning package to impute missing SNPs |
2023-07-23 01:31:36 |
| vae-anomaly-detection |
2.0.0 |
Pytorch/TF1 implementation of Variational AutoEncoder for anomaly detection following the paper "Variational Autoencoder based Anomaly Detection using Reconstruction Probability by Jinwon An, Sungzoon Cho" |
2023-03-18 11:10:48 |
| Coupled-VAE |
0.0.1 |
Package holding code for Coupled VAE paper. |
2023-01-05 04:06:29 |