| AntixK/PyTorch-VAE |
5,292 |
|
0 |
0 |
over 2 years ago |
0 |
|
48 |
apache-2.0 |
Python |
| A Collection of Variational Autoencoders (VAE) in PyTorch. |
| mdeff/fma |
1,773 |
|
0 |
0 |
over 3 years ago |
0 |
|
10 |
mit |
Jupyter Notebook |
| FMA: A Dataset For Music Analysis |
| wenbihan/reproducible-image-denoising-state-of-the-art |
1,759 |
|
0 |
0 |
over 4 years ago |
0 |
|
4 |
|
|
| Collection of popular and reproducible image denoising works. |
| JavierAntoran/Bayesian-Neural-Networks |
1,633 |
|
0 |
0 |
over 2 years ago |
0 |
|
5 |
mit |
Jupyter Notebook |
| Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more |
| MaurizioFD/RecSys2019_DeepLearning_Evaluation |
871 |
|
0 |
0 |
about 4 years ago |
0 |
|
1 |
agpl-3.0 |
Python |
| This is the repository of our article published in RecSys 2019 "Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches" and of several follow-up studies. |
| YannDubs/disentangling-vae |
668 |
|
0 |
0 |
about 3 years ago |
0 |
|
7 |
other |
Python |
| Experiments for understanding disentanglement in VAE latent representations |
| G-U-N/PyCIL |
613 |
|
0 |
0 |
about 2 years ago |
0 |
|
3 |
other |
Python |
| PyCIL: A Python Toolbox for Class-Incremental Learning |
| NVlabs/sionna |
534 |
|
0 |
4 |
over 2 years ago |
15 |
December 08, 2023 |
9 |
other |
Jupyter Notebook |
| Sionna: An Open-Source Library for Next-Generation Physical Layer Research |
| mmasana/FACIL |
425 |
|
0 |
0 |
almost 3 years ago |
0 |
|
9 |
mit |
Python |
| Framework for Analysis of Class-Incremental Learning with 12 state-of-the-art methods and 3 baselines. |
| minerva-ml/steppy |
136 |
|
5 |
0 |
over 7 years ago |
16 |
November 23, 2018 |
16 |
mit |
Python |
| Lightweight, Python library for fast and reproducible experimentation :microscope: |
