Structure-aware interactive graph neural networks for the prediction of protein-ligand binding affinity
Drug discovery often relies on the successful prediction of protein-ligand binding affinity.
Recent advances have shown great promise in applying graph neural networks (GNNs) for …
Recent advances have shown great promise in applying graph neural networks (GNNs) for …
Deep learning for trajectory data management and mining: A survey and beyond
Trajectory computing is a pivotal domain encompassing trajectory data management and
mining, garnering widespread attention due to its crucial role in various practical …
mining, garnering widespread attention due to its crucial role in various practical …
A survey of route recommendations: Methods, applications, and opportunities
Nowadays, with advanced information technologies deployed citywide, large data volumes
and powerful computational resources are intelligentizing modern city development. As an …
and powerful computational resources are intelligentizing modern city development. As an …
Intelligent electric vehicle charging recommendation based on multi-agent reinforcement learning
Electric Vehicle (EV) has become a preferable choice in the modern transportation system
due to its environmental and energy sustainability. However, in many large cities, EV drivers …
due to its environmental and energy sustainability. However, in many large cities, EV drivers …
Joint air quality and weather prediction based on multi-adversarial spatiotemporal networks
Accurate and timely air quality and weather predictions are of great importance to urban
governance and human livelihood. Though many efforts have been made for air quality or …
governance and human livelihood. Though many efforts have been made for air quality or …
Leaving no one behind: A multi-scenario multi-task meta learning approach for advertiser modeling
Advertisers play an essential role in many e-commerce platforms like Taobao and Amazon.
Fulfilling their marketing needs and supporting their business growth is critical to the long …
Fulfilling their marketing needs and supporting their business growth is critical to the long …
Times series forecasting for urban building energy consumption based on graph convolutional network
The world is increasingly urbanizing, and to improve urban sustainability, many cities adopt
ambitious energy-saving strategies through retrofitting existing buildings and constructing …
ambitious energy-saving strategies through retrofitting existing buildings and constructing …
Kill two birds with one stone: A multi-view multi-adversarial learning approach for joint air quality and weather prediction
Accurate and timely air quality and weather predictions are of great importance to urban
governance and human livelihood. Though many efforts have been made for air quality or …
governance and human livelihood. Though many efforts have been made for air quality or …
Modality matches modality: Pretraining modality-disentangled item representations for recommendation
Recent works have shown the effectiveness of incorporating textual and visual information to
tackle the sparsity problem in recommendation scenarios. To fuse these useful …
tackle the sparsity problem in recommendation scenarios. To fuse these useful …
Lightpath: Lightweight and scalable path representation learning
Movement paths are used widely in intelligent transportation and smart city applications. To
serve such applications, path representation learning aims to provide compact …
serve such applications, path representation learning aims to provide compact …