Found 65 presentations matching your search
this contains the research papers
DSTAGNN: Dynamic Spatial-Temporal Aware Graph Neural Network for Traffic Flow Forecasting
Towards Dynamic Spatial-Temporal Graph Learning: A Decoupled Perspective
Graph Representation Learning Meets Computer Vision: A Survey
Learning Decomposed Spatial Relations for Multi-Variate Time-Series Modeling
Forecasting COVID-19 Dynamics: Clustering, Generalized Spatiotemporal Attention, and Impacts of Mobi...
TelTrans: Applying Multi-Type Telecom Data to Transportation Evaluation and Prediction via Multiface...
Lightning is an electrical discharge caused by imbalances between storm clouds and the ground, or w...
PDFormer: Propagation Delay-Aware Dynamic Long-Range Transformer for Traffic Flow Prediction
GinAR: An End-To-End Multivariate Time Series Forecasting Model Suitable for Variable Missing
Podo smart a physiotherapy device
scm
MFTraj: Map-Free, Behavior-Driven Trajectory Prediction for Autonomous Driving
Applying bioinformatics and statistical genetics methods on population data to understand the mechan...
1ST LEVEL PROJECT
The complexity of both natural and technological systems has reduced the ability of humans to monito...
Invited Keynote UC San Diego Jacobs School of Engineering Dean’s Council of Advisors Meeting UC Sa...
Application of Internet of Things in Agriculture
EAA2024 Rome presentation in session #381 "Capacity Building for FAIR Data Sharing and Digital ...
This technical report performs a rigorous comparative evaluation of advanced geostatistical methods ...
opyical view
This seminar presentation is prepared as part of the Course requirement of HSM621 Seminar and Practi...
Doing in One Go: Delivery Time Inference Based on Couriers’ Trajectories
Geoscience
![[20240520_LabSeminar_Huy]DSTAGNN: Dynamic Spatial-Temporal Aware Graph Neural Network for Traffic Flow Forecasting.pptx](https://slidepub.com/thumb/1507/268771507.jpg)
![[20240624_LabSeminar_Huy]Towards Dynamic Spatial-Temporal Graph Learning: A Decoupled Perspective.pptx](https://slidepub.com/thumb/9528/269849528.jpg)
![[NS][Lab_Seminar_240610]Graph Representation Learning Meets Computer Vision: A Survey.pptx](https://slidepub.com/thumb/9561/269849561.jpg)
![[20240819_LabSeminar_Huy]Learning Decomposed Spatial Relations for Multi-Variate Time-Series Modeling.pptx](https://slidepub.com/thumb/9665/271139665.jpg)
![[20240708_LabSeminar_Huy]Covid19Dynamics.pptx](https://slidepub.com/thumb/2888/270122888.jpg)
![[20240701_LabSeminar_Huy]TelTrans: Applying Multi-Type Telecom Data to Transportation Evaluation and Prediction via Multifaceted Graph Modeling.pptx](https://slidepub.com/thumb/6994/270006994.jpg)
![[20240710_LabSeminar_Huy]PDFormer: Propagation Delay-Aware Dynamic Long-Range Transformer for Traffic Flow Prediction.pptx](https://slidepub.com/thumb/3004/270433004.jpg)
![[20240930_LabSeminar_Huy]GinAR: An End-To-End Multivariate Time Series Forecasting Model Suitable for Variable Missing.pptx](https://slidepub.com/thumb/6004/272106004.jpg)
![[2024107_LabSeminar_Huy]MFTraj: Map-Free, Behavior-Driven Trajectory Prediction for Autonomous Driving.pptx](https://slidepub.com/thumb/5909/272285909.jpg)
