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07/19/2023
LightPath: Lightweight and Scalable Path Representation Learning
Movement paths are used widely in intelligent transportation and smart c...
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06/08/2023
A Crystal-Specific Pre-Training Framework for Crystal Material Property Prediction
Crystal property prediction is a crucial aspect of developing novel mate...
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02/24/2023
LightTS: Lightweight Time Series Classification with Adaptive Ensemble Distillation – Extended Version
Due to the sweeping digitalization of processes, increasingly vast amoun...
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12/20/2022
A Pattern Discovery Approach to Multivariate Time Series Forecasting
Multivariate time series forecasting constitutes important functionality...
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12/08/2022
AutoPINN: When AutoML Meets Physics-Informed Neural Networks
Physics-Informed Neural Networks (PINNs) have recently been proposed to ...
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11/29/2022
Joint Neural Architecture and Hyperparameter Search for Correlated Time Series Forecasting
Sensors in cyber-physical systems often capture interconnected processes...
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09/10/2022
A Comparative Study on Unsupervised Anomaly Detection for Time Series: Experiments and Analysis
The continued digitization of societal processes translates into a proli...
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04/28/2022
Triformer: Triangular, Variable-Specific Attentions for Long Sequence Multivariate Time Series Forecasting–Full Version
A variety of real-world applications rely on far future information to m...
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04/07/2022
Robust and Explainable Autoencoders for Unsupervised Time Series Outlier Detection—Extended Version
Time series data occurs widely, and outlier detection is a fundamental p...
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03/30/2022
Weakly-supervised Temporal Path Representation Learning with Contrastive Curriculum Learning – Extended Version
In step with the digitalization of transportation, we are witnessing a g...
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03/29/2022
Towards Spatio-Temporal Aware Traffic Time Series Forecasting–Full Version
Traffic time series forecasting is challenging due to complex spatio-tem...
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12/21/2021
AutoCTS: Automated Correlated Time Series Forecasting – Extended Version
Correlated time series (CTS) forecasting plays an essential role in many...
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11/22/2021
Unsupervised Time Series Outlier Detection with Diversity-Driven Convolutional Ensembles – Extended Version
With the sweeping digitalization of societal, medical, industrial, and s...
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06/17/2021
Unsupervised Path Representation Learning with Curriculum Negative Sampling
Path representations are critical in a variety of transportation applica...
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03/19/2021
Graph Attention Recurrent Neural Networks for Correlated Time Series Forecasting – Full version
We consider a setting where multiple entities inter-act with each other ...
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11/13/2018
Recurrent Multi-Graph Neural Networks for Travel Cost Prediction
Origin-destination (OD) matrices are often used in urban planning, where...
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08/29/2018
Correlated Time Series Forecasting using Deep Neural Networks: A Summary of Results
Cyber-physical systems often consist of entities that interact with each...
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02/22/2018
