Made
MADE: Masked Autoencoder for Distribution Estimation
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Alae | 2,850 | 3 years ago | 31 | Python | ||||||
| [CVPR2020] Adversarial Latent Autoencoders | ||||||||||
| Deepsvg | 829 | 3 months ago | 28 | mit | Jupyter Notebook | |||||
| [NeurIPS 2020] Official code for the paper "DeepSVG: A Hierarchical Generative Network for Vector Graphics Animation". Includes a PyTorch library for deep learning with SVG data. | ||||||||||
| Nvae | 826 | a year ago | 25 | other | Python | |||||
| The Official PyTorch Implementation of "NVAE: A Deep Hierarchical Variational Autoencoder" (NeurIPS 2020 spotlight paper) | ||||||||||
| Pytorch_cpp | 215 | 10 months ago | 5 | mit | C++ | |||||
| Deep Learning sample programs using PyTorch in C++ | ||||||||||
| Awesome Tensorlayer | 212 | 4 years ago | 1 | cc0-1.0 | ||||||
| A curated list of dedicated resources and applications | ||||||||||
| Motion Sense | 189 | 3 years ago | 2 | mit | Jupyter Notebook | |||||
| MotionSense Dataset for Human Activity and Attribute Recognition ( time-series data generated by smartphone's sensors: accelerometer and gyroscope) (PMC Journal) (IoTDI'19) | ||||||||||
| Mvtec Anomaly Detection | 162 | 2 years ago | 21 | Python | ||||||
| This project proposes an end-to-end framework for semi-supervised Anomaly Detection and Segmentation in images based on Deep Learning. | ||||||||||
| Oneshottranslation | 126 | 5 years ago | 1 | other | Python | |||||
| Pytorch implementation of "One-Shot Unsupervised Cross Domain Translation" NIPS 2018 | ||||||||||
| Unsupervised_anomaly_detection_brain_mri | 123 | 2 years ago | 1 | gpl-3.0 | Python | |||||
| Autoencoders for Unsupervised Anomaly Segmentation in Brain MR Images: A Comparative Study | ||||||||||
| Visualml | 106 | a year ago | 11 | gpl-3.0 | CSS | |||||
| Interactive Visual Machine Learning Demos. | ||||||||||
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