Stars
TensorFlow code and pre-trained models for BERT
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Implementation of unified embedding model from Embedding-based Retrieval in Facebook Search.
Research works on different versions of IntentGC and several state-of-the-art algorithms on public amazon data
Tensorflow2.0 🍎🍊 is delicious, just eat it! 😋😋
CTR prediction models based on deep learning(基于深度学习的广告推荐CTR预估模型)
A TensorFlow Keras implementation of "Modeling Task Relationships in Multi-task Learning with Multi-gate Mixture-of-Experts" (KDD 2018)
Python package built to ease deep learning on graph, on top of existing DL frameworks.
Pytorch implementation of the Graph Attention Network model by Veličković et. al (2017, https://arxiv.org/abs/1710.10903)
Graph Convolutional Networks for Text Classification. AAAI 2019
Framework for evaluating Graph Neural Network models on semi-supervised node classification task
A PyTorch implementation of "Graph Classification Using Structural Attention" (KDD 2018).
Graph Neural Network Library for PyTorch
Implementation of Graph Convolutional Networks in TensorFlow
Pytorch Implementation for Graph Convolutional Neural Networks
PyTorch Tutorial for Deep Learning Researchers
A flexible package for multimodal-deep-learning to combine tabular data with text and images using Wide and Deep models in Pytorch
SEAL (learning from Subgraphs, Embeddings, and Attributes for Link prediction). "M. Zhang, Y. Chen, Link Prediction Based on Graph Neural Networks, NeurIPS 2018 spotlight".
This repository provides a reference implementation of struc2vec.
Repo for counting stars and contributing. Press F to pay respect to glorious developers.
Pedagogical example realization of wide & deep networks, using TensorFlow and TFLearn.
Random generator via atmospheric noise random.org