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09/08/2023
Navigating Out-of-Distribution Electricity Load Forecasting during COVID-19: A Continual Learning Approach Leveraging Human Mobility
In traditional deep learning algorithms, one of the key assumptions is t...
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06/10/2023
Continually learning out-of-distribution spatiotemporal data for robust energy forecasting
Forecasting building energy usage is essential for promoting sustainabil...
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05/09/2023
Message Passing Neural Networks for Traffic Forecasting
A road network, in the context of traffic forecasting, is typically mode...
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05/09/2023
Traffic Forecasting on New Roads Unseen in the Training Data Using Spatial Contrastive Pre-Training
New roads are being constructed all the time. However, the capabilities ...
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02/20/2023
Because Every Sensor Is Unique, so Is Every Pair: Handling Dynamicity in Traffic Forecasting
Traffic forecasting is a critical task to extract values from cyber-phys...
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05/19/2021
Predicting Flight Delay with Spatio-Temporal Trajectory Convolutional Network and Airport Situational Awareness Map
To model and forecast flight delays accurately, it is crucial to harness...
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08/18/2020
Generative Adversarial Networks for Spatio-temporal Data: A Survey
Generative Adversarial Networks (GANs) have shown remarkable success in ...
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11/05/2019
Flight Delay Prediction using Airport Situational Awareness Map
The prediction of flight delays plays a significantly important role for...
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09/24/2019