nidohsp Goto Github PK

colossalai

Making large AI models cheaper, faster and more accessible

deepst

Reconstruction of DeepST

few-shot-ssl-public

Meta Learning for Semi-Supervised Few-Shot Classification

flashback_code

fmlp-rec

gcn-pytorch

Graph Convolution Network for PyTorch

ics

智能计算系统课程（陈云霁）课后作业记录

lstpm

Ke Sun, Tieyun Qian, Tong Chen, Yile Liang, Quoc Viet Hung Nguyen, Hongzhi Yin: Where to Go Next: Modeling Long- and Short-Term User Preferences for Point-of-Interest Recommendation. AAAI 2020 accepted.

mecos-tf

Meta-learning-based Cold-Start Sequential Recommendation

prme

Implementation of the Personalized Ranking Metric Embedding for Next New POI Recommendation

spatial-temporal-attention-network-for-poi-recommendation

Codes for a WWW'21 Paper. A state-of-the-art recommender system for location/trajectory prediction.

st-lstm_pytorch

ST-LSTM network implemented using PyTorch.

st-metanet

The codes and data of paper "Urban Traffic Prediction from Spatio-Temporal Data Using Deep Meta Learning"

strnn

Predicting the Next Location: A Recurrent Model with Spatial and Temporal Contexts

traffic_prediction

Traffic prediction is the task of predicting future traffic measurements (e.g. volume, speed, etc.) in a road network (graph), using historical data (timeseries).