Qitong Hu's Projects
A library to detect emotions from text using supervised learning techniques
TensorFlow Code for paper "Efficient Neural Architecture Search via Parameter Sharing"
PyTorch implementation of "Efficient Neural Architecture Search via Parameters Sharing"
Deal or No Deal? End-to-End Learning for Negotiation Dialogues
ICASSP2017: End-to-end joint learning of natural language understanding and dialogue manager
ECCV18 Workshops - Enhanced SRGAN. Champion PIRM Challenge on Perceptual Super-Resolution (Third Region)
TensorFlow examples
Real-time face detection and emotion/gender classification using fer2013/imdb datasets with a keras CNN model and openCV.
Non official project based on original /r/Deepfakes thread. Many thanks to him!
Visualizations for machine learning datasets
Facial-Expression-Recognition in TensorFlow. Detecting faces in video and recognize the expression(emotion).
Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
Fast, Accurate and Lightweight Super-Resolution models
A Toolkit for Chinese Topic Modeling
TensorFlow CNN for fast style transfer! ⚡🖥🎨🖼
The fast.ai deep learning library, lessons, and tutorials
segmentation, instance segmentation and single image depth
Library for fast text representation and classification.
Code and model for the paper "Improving Language Understanding by Generative Pre-Training"
A very simple framework for state-of-the-art NLP
A Chinese Nature Language Toolkit
A neural network toolkit for Metal
starter from "How to Train a GAN?" at NIPS2016
Companion repository to GANs in Action: Deep learning with Generative Adversarial Networks
Sample Code for Gated Graph Neural Networks
A tutorial on Graph Convolutional Neural Networks
Annotated, understandable, and visually interpretable PyTorch implementations of: VAE, BIRVAE, NSGAN, MMGAN, WGAN, WGANGP, LSGAN, DRAGAN, BEGAN, RaGAN, InfoGAN, fGAN, FisherGAN
Gibson Environments: Real-World Perception for Embodied Agents
Code for reproducing results in "Glow: Generative Flow with Invertible 1x1 Convolutions"
Must-read papers on graph neural networks (GNN)