| podgorskiy/ALAE |
2,850 |
|
0 |
0 |
about 5 years ago |
0 |
|
31 |
|
Python |
| [CVPR2020] Adversarial Latent Autoencoders |
| alexandre01/deepsvg |
829 |
|
0 |
0 |
about 2 years ago |
0 |
|
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. |
| NVlabs/NVAE |
826 |
|
0 |
0 |
over 3 years ago |
0 |
|
25 |
other |
Python |
| The Official PyTorch Implementation of "NVAE: A Deep Hierarchical Variational Autoencoder" (NeurIPS 2020 spotlight paper) |
| koba-jon/pytorch_cpp |
215 |
|
0 |
0 |
almost 3 years ago |
0 |
|
5 |
mit |
C++ |
| Deep Learning sample programs using PyTorch in C++ |
| tensorlayer/awesome-tensorlayer |
212 |
|
0 |
0 |
about 6 years ago |
0 |
|
1 |
cc0-1.0 |
|
| A curated list of dedicated resources and applications |
| mmalekzadeh/motion-sense |
189 |
|
0 |
0 |
over 4 years ago |
0 |
|
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) |
| AdneneBoumessouer/MVTec-Anomaly-Detection |
162 |
|
0 |
0 |
about 4 years ago |
0 |
|
21 |
|
Python |
| This project proposes an end-to-end framework for semi-supervised Anomaly Detection and Segmentation in images based on Deep Learning. |
| sagiebenaim/OneShotTranslation |
126 |
|
0 |
0 |
about 7 years ago |
0 |
|
1 |
other |
Python |
| Pytorch implementation of "One-Shot Unsupervised Cross Domain Translation" NIPS 2018 |
| StefanDenn3r/Unsupervised_Anomaly_Detection_Brain_MRI |
123 |
|
0 |
0 |
over 3 years ago |
0 |
|
1 |
gpl-3.0 |
Python |
| Autoencoders for Unsupervised Anomaly Segmentation in Brain MR Images: A Comparative Study |
| dsgiitr/VisualML |
106 |
|
0 |
0 |
about 3 years ago |
0 |
|
11 |
gpl-3.0 |
CSS |
| Interactive Visual Machine Learning Demos. |
