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fairseq-1

Facebook AI Research Sequence-to-Sequence Toolkit written in Python.

gae

Implementation of Graph Auto-Encoders in TensorFlow

ganhacks

starter from "How to Train a GAN?" at NIPS2016

google-research

Google Research

gryffin

gsn

Efficient implementation of Generative Stochastic Networks

gsn-1

Implementation of Generative Stochastic Networks in TensorFlow

hyperas

Keras + Hyperopt: A very simple wrapper for convenient hyperparameter optimization

idec

immucc

Cell-Centric View of Tissue Transcriptome Measuring Cellular Compositions of Immune Microenvironment From Mouse RNA-Seq Data.

joint-cluster-cnn

A tensorflow version of JULE (Joint Unsupervised Learning of Deep Representations and Image Clusters).

jule.torch

Torch code for our CVPR 2016 paper "Joint Unsupervised LEarning of Deep Representations and Image Clusters"

keras

Deep Learning library for Python. Runs on TensorFlow, Theano, or CNTK.

keras-adversarial

Keras Generative Adversarial Networks

keras-attention

Visualizing RNNs using the attention mechanism

keras-attention-mechanism

Attention mechanism Implementation for Keras.

keras-dcgan

Keras implementation of Deep Convolutional Generative Adversarial Networks

keras-gan

Generative Adversarial Network with Keras (Theano backend)

keras-gan-1

Keras implementations of Generative Adversarial Networks.

keras-monotonic-attention

seq2seq attention in keras

keras-transformer

Keras library for building (Universal) Transformers, facilitating BERT and GPT models

keras-transformer-1

Transformer implemented in Keras

labelme

Image Polygonal Annotation with Python (polygon, rectangle, circle, line, point and image-level flag annotation).

lda2vec

lda2vec-tf

tensorflow port of the lda2vec model for unsupervised learning of document + topic + word embeddings

memory_profiler

Monitor Memory usage of Python code

mulocdeep

mulocdeepweb

multilateration

Implementation of the Information Content Heuristic (ICH) algorithm and code for constructing resolving sets on Hamming graphs

musite

Musite is a Java-based standalone application for predicting both general and kinase-specific protein phosphorylation sites. Musite 1.0 pre-trained prediction models for 6 eukaryotic organisms: Homo sapiens, Mus musculus, Drosophila melanogaster, Caenorhabditis elegans, Saccharomyces cerevisiae, and Arabidopsis thaliana. It is advisable to train your own prediction models from your specific training data, using the customized model training tool in Musite.