To handle graphs in which features or connectivities are evolving over t...
The field of urban spatial-temporal prediction is advancing rapidly with...
As deep learning technology advances and more urban spatial-temporal dat...
Multimodal magnetic resonance imaging (MRI) can reveal different pattern...
Deep unfolding networks (DUNs) are the foremost methods in the realm of
...
In this technical report, we present our solution for the Baidu KDD Cup ...
As a core technology of Intelligent Transportation System, traffic flow
...
Simulating the human mobility and generating large-scale trajectories ar...
Trajectory Representation Learning (TRL) is a powerful tool for
spatial-...
High-performance traffic flow prediction model designing, a core technol...
Vertical federated learning (VFL) is an emerging paradigm that allows
di...
Stochastic gradient descent (SGD) is the cornerstone of modern machine
l...
Detecting fraudulent transactions is an essential component to control r...
The ensemble of deep neural networks has been shown, both theoretically ...
The appeal of serverless (FaaS) has triggered a growing interest on how ...
Gradient boosting decision tree (GBDT) is a widely-used machine learning...
The performance of deep neural networks crucially depends on good
hyperp...