This is the homepage of a new book entitled "Mathematical Foundations of Reinforcement Learning."

A framework for large scale recommendation algorithms.

a easy pytorch implement of GeoMAN

Code for the IJCAI'19 paper "Deep Session Interest Network for Click-Through Rate Prediction"

Temporal Graph Convolutional Network for Urban Traffic Flow Prediction Method

An open autonomous driving platform

LibCity: An Open Library for Urban Spatio-temporal Data Mining

An Open-source Toolkit for Deep Learning based Recommendation with Tensorflow.

This is the repository for the collection of Graph Neural Network for Traffic Forecasting.

Achieve a tiny STL in C++11

2021科大讯飞-车辆贷款违约预测挑战赛 Top1方案

Attention Based Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting, AAAI 2019, pytorch version

This is a Pytorch implementation of ASTGNN. Now the corresponding paper is available online at https://ieeexplore.ieee.org/document/9346058.

A fork of youtube-dl, for archival purposes.

This repo includes introduction, code and dataset of our paper Deep Sequence Learning with Auxiliary Information for Traffic Prediction (KDD 2018).

A TensorFlow Implementation of Deep Spatio-Temporal Residual Networks (ST-ResNet): https://arxiv.org/abs/1610.00081

手把手撕LeetCode题目，扒各种算法套路的裤子。English version supported! Crack LeetCode, not only how, but also why.

A Tensorflow Implementation of Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction

Reconstruction of DeepST

TTI ,Smart Transportation Industry Standard

PyTorch implementation of Multi-Label Image Recognition with Graph Convolutional Networks, CVPR 2019.

Tensorflow 1 implementation of paper https://www.ijcai.org/proceedings/2018/0476.pdf

CTR prediction models based on deep learning(基于深度学习的广告推荐CTR预估模型)

PySpark-Tutorial provides basic algorithms using PySpark

Tensorflow implementation of paper http://arxiv.org/abs/1809.02105

Tensorflow implementation of paper http://arxiv.org/abs/1704.02971

Code for WWW'19 "Unbiased LambdaMART: An Unbiased Pairwise Learning-to-Rank Algorithm", which is based on LightGBM

Source code for KDD 2018 paper "Leverage Meta-path based Context for Top-N Recommendation with a Neural Co-Attention Model"

RNN示例集合