reinforcement-learningoptimizationsurveyknowledge-graph-embeddingtemporal-knowledge-graph UpdatedSep 10, 2024 Python The official repo of TimeLlama, an instruction-finetuned Llama2 series that improve complex temporal reasoning ability. natural-language-processingknowledge-graphtemporal-reasoningevent-forecastingexp...
8. Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting 作者:Bing Yu, et al. (Peking University) 发表时间:2018 发表于:IJCAI 2018 关键词:时空图,交通流量预测,DTDG 概述:作者将交通流量预测建模为时空图(Spatial- Temporal Graph)的形式,设计了一种能够在时空图...
(events)that happened at different timestamps have different influences on future events,which can be attributed to a hierarchy among not only facts but also relevant entities.Therefore,it is crucial to pay more attention to important entities and events when forecasting the future.However,most ...
Forecasting Interaction Order on Temporal Graphs (KDD, 2021) Temporal Knowledge Graph Reasoning Based on Evolutional Representation Learning (SIGIR, 2021) [paper][code] Inductive Representation Learning in Temporal Networks via Mining Neighborhood and Community Influences (SIGIR, 2021) TIE: A Framework fo...
时空知识图谱,顾名思义,是具有地理时空分布或位置隐喻的知识构成的有向图,即以时空分布特征为核心的知识图谱(Spatial-temporal Knowledge Graph,或Geo-related Knowledge Graph,以下简称GeoKG)。GeoKG旨在通过计算机规范化表达与存储与地理时空分布相关的知识集合,进而支持地理时空分布或位置相关知识检索与知识推理。其中的图...
Spatio-Temporal Graph Few-Shot Learning with Cross-City Knowledge Transfer sofiaeyeln 334 0 When Transfer Learning Meets Cross-City Urban Flow Prediction: Spatio-Temporal A sofiaeyeln 162 0 PDF:Periodicity decoupling framework for long-time series forecasting sofiaeyeln 183 0 U-Mixer: An Unet...
1. Spatial-Temporal-Decoupled Masked Pre-training for Spatiotemporal Forecasting 链接:https://arxiv.org/abs/2312.00516 代码:https://github.com/Jimmy-7664/STD-MAE 作者:Haotian Gao, Renhe Jiang, Zheng Dong, Jinliang Deng, Yuxin Ma, Xuan Song ...
Forecasting Interaction Order on Temporal Graphs (KDD, 2021) Temporal Knowledge Graph Reasoning Based on Evolutional Representation Learning (SIGIR, 2021) [paper][code] Inductive Representation Learning in Temporal Networks via Mining Neighborhood and Community Influences (SIGIR, 2021) ...
We first construct a city knowledge graph for traffic forecasting, then use KS-Cells to combine the information from the knowledge graph and the traffic network, and finally, capture the temporal changes of the traffic state with GRU. Testing on real-world datasets shows that the KST-GCN has ...
12 Spatio-Temporal Transformer Network with Physical Knowledge Distillation for Weather Forecasting 13 Hierarchical Spatio-Temporal Graph Learning Based on Metapath Aggregation for Emergency Supply Forecasting 14 Urban Traffic Accident Risk Prediction Revisited: Regionality, Proximity, Similarity and Sparsity 15...