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09/13/2023
Uncertainty-aware Traffic Prediction under Missing Data
Traffic prediction is a crucial topic because of its broad scope of appl...
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06/19/2023
FDTI: Fine-grained Deep Traffic Inference with Roadnet-enriched Graph
This paper proposes the fine-grained traffic prediction task (e.g. inter...
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02/24/2023
Few-Shot Table-to-Text Generation with Prompt-based Adapter
Pre-trained language models (PLMs) have made remarkable progress in tabl...
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02/09/2023
Few-Shot Table-to-Text Generation with Prompt Planning and Knowledge Memorization
Pre-trained language models (PLM) have achieved remarkable advancement i...
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10/03/2022
CBLab: Scalable Traffic Simulation with Enriched Data Supporting
Traffic simulation provides interactive data for the optimization of tra...
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12/11/2021
MedAttacker: Exploring Black-Box Adversarial Attacks on Risk Prediction Models in Healthcare
Deep neural networks (DNNs) have been broadly adopted in health risk pre...
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05/20/2021
Objective-aware Traffic Simulation via Inverse Reinforcement Learning
Traffic simulators act as an essential component in the operating and pl...
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05/18/2021
Learning to Route via Theory-Guided Residual Network
The heavy traffic and related issues have always been concerns for moder...
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03/22/2021
Learning to Simulate on Sparse Trajectory Data
Simulation of the real-world traffic can be used to help validate the tr...
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09/17/2020
GeneraLight: Improving Environment Generalization of Traffic Signal Control via Meta Reinforcement Learning
The heavy traffic congestion problem has always been a concern for moder...
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08/29/2019
Targeted Source Detection for Environmental Data
In the face of growing needs for water and energy, a fundamental underst...
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05/12/2019
Learning Phase Competition for Traffic Signal Control
Increasingly available city data and advanced learning techniques have e...
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05/12/2019
Diagnosing Reinforcement Learning for Traffic Signal Control
With the increasing availability of traffic data and advance of deep rei...
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05/11/2019
CoLight: Learning Network-level Cooperation for Traffic Signal Control
Cooperation is critical in multi-agent reinforcement learning (MARL). In...
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04/17/2019
A Survey on Traffic Signal Control Methods
Traffic signal control is an important and challenging real-world proble...
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03/03/2018
