Traffic prediction is a crucial topic because of its broad scope of
appl...
This paper proposes the fine-grained traffic prediction task (e.g. inter...
Pre-trained language models (PLMs) have made remarkable progress in
tabl...
Pre-trained language models (PLM) have achieved remarkable advancement i...
Traffic simulation provides interactive data for the optimization of tra...
Deep neural networks (DNNs) have been broadly adopted in health risk
pre...
Traffic simulators act as an essential component in the operating and
pl...
The heavy traffic and related issues have always been concerns for moder...
Simulation of the real-world traffic can be used to help validate the
tr...
The heavy traffic congestion problem has always been a concern for moder...
In the face of growing needs for water and energy, a fundamental
underst...
Increasingly available city data and advanced learning techniques have
e...
With the increasing availability of traffic data and advance of deep
rei...
Cooperation is critical in multi-agent reinforcement learning (MARL). In...
Traffic signal control is an important and challenging real-world proble...
Spatial-temporal prediction has many applications such as climate foreca...