Traffic prediction is a crucial topic because of its broad scope of
appl...
Numerous solutions are proposed for the Traffic Signal Control (TSC) tas...
Traffic management systems play a vital role in ensuring safe and effici...
Traffic signal control (TSC) is a complex and important task that affect...
Graph regression is a fundamental task and has received increasing atten...
Graph Neural Networks (GNNs) have received increasing attention due to t...
This paper proposes the fine-grained traffic prediction task (e.g. inter...
The emergence of reinforcement learning (RL) methods in traffic signal
c...
Single occupancy vehicles are the most attractive transportation alterna...
Traffic signal control is safety-critical for our daily life. Roughly
on...
This paper introduces a library for cross-simulator comparison of
reinfo...
Modeling how network-level traffic flow changes in the urban environment...
Most dialogue systems in real world rely on predefined intents and answe...
Offline reinforcement learning (RL) tries to learn the near-optimal poli...
Simulation of the real-world traffic can be used to help validate the
tr...
Modeling how human moves on the space is useful for policy-making in
tra...
Connecting consumers with relevant products is a very important problem ...
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...