Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
---|---|---|---|---|---|---|---|---|---|---|
Deepjazz | 2,583 | 4 years ago | 12 | apache-2.0 | Python | |||||
Deep learning driven jazz generation using Keras & Theano! | ||||||||||
Fast Wavenet | 1,620 | 6 years ago | 15 | gpl-3.0 | Python | |||||
Speedy Wavenet generation using dynamic programming :zap: | ||||||||||
Texar Pytorch | 711 | 1 | 1 | a year ago | 5 | April 14, 2022 | 36 | apache-2.0 | Python | |
Integrating the Best of TF into PyTorch, for Machine Learning, Natural Language Processing, and Text Generation. This is part of the CASL project: http://casl-project.ai/ | ||||||||||
Awesome Question Answering | 658 | 10 days ago | ||||||||
Resources, datasets, papers on Question Answering | ||||||||||
Model Card Toolkit | 344 | 2 months ago | 10 | April 28, 2022 | 10 | apache-2.0 | Python | |||
A toolkit that streamlines and automates the generation of model cards | ||||||||||
Voicebook | 325 | 4 months ago | 19 | apache-2.0 | Python | |||||
🗣️ A book and repo to get you started programming voice computing applications in Python (10 chapters and 200+ scripts). | ||||||||||
Awesome Diffusion Models In Medical Imaging | 318 | 2 days ago | mit | |||||||
Diffusion Models in Medical Imaging | ||||||||||
Muspy | 268 | 1 | a year ago | 6 | April 16, 2022 | 15 | mit | Python | ||
A toolkit for symbolic music generation | ||||||||||
Scene_generation | 145 | 2 years ago | 6 | apache-2.0 | Python | |||||
A PyTorch implementation of the paper: Specifying Object Attributes and Relations in Interactive Scene Generation | ||||||||||
Lffont | 106 | 8 months ago | other | Python | ||||||
Official PyTorch implementation of LF-Font (Few-shot Font Generation with Localized Style Representations and Factorization) AAAI 2021 |
Automated cryptographic classification framework using Intel's Pin platform for dynamic binary instrumentation and PyTorch for deep learning.
sudo apt-get install python-pip python-tk
pip install -r requirements.txt
python knight.py --setup
sudo apt install libssl-dev
Automatically draw distribution:
python crypto.py -d scale
Evaluatation:
python knight.py --predict <executable>
python knight.py --evaluate <dataset>
To add custom cryptographic samples to the generation pool, please follow the Format Specification.
We also published "CryptoKnight: Generating and Modelling Compiled Cryptographic Primitives " that can be found here in Open Access.
If you want to cite the paper please use the following format;
@Article{info9090231,
AUTHOR = {Hill, Gregory and Bellekens, Xavier},
TITLE = {CryptoKnight: Generating and Modelling Compiled Cryptographic Primitives},
JOURNAL = {Information},
VOLUME = {9},
YEAR = {2018},
NUMBER = {9},
ARTICLE NUMBER = {231},
URL = {http://www.mdpi.com/2078-2489/9/9/231},
ISSN = {2078-2489},
DOI = {10.3390/info9090231}
}