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07/24/2023
Rethinking Data Distillation: Do Not Overlook Calibration
Neural networks trained on distilled data often produce over-confident o...
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01/20/2023
STORM-GAN: Spatio-Temporal Meta-GAN for Cross-City Estimation of Human Mobility Responses to COVID-19
Human mobility estimation is crucial during the COVID-19 pandemic due to...
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01/13/2023
Eco-PiNN: A Physics-informed Neural Network for Eco-toll Estimation
The eco-toll estimation problem quantifies the expected environmental co...
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12/10/2022
Task-Adaptive Meta-Learning Framework for Advancing Spatial Generalizability
Spatio-temporal machine learning is critically needed for a variety of s...
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02/11/2022
Modeling Reservoir Release Using Pseudo-Prospective Learning and Physical Simulations to Predict Water Temperature
This paper proposes a new data-driven method for predicting water temper...
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03/22/2021
Statistically-Robust Clustering Techniques for Mapping Spatial Hotspots: A Survey
Mapping of spatial hotspots, i.e., regions with significantly higher rat...
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11/17/2020