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07/31/2023
A Pre-trained Data Deduplication Model based on Active Learning
In the era of big data, the issue of data quality has become increasingl...
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08/29/2022
A Missing Value Filling Model Based on Feature Fusion Enhanced Autoencoder
With the advent of the big data era, the data quality problem is becomin...
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06/11/2022
DRAformer: Differentially Reconstructed Attention Transformer for Time-Series Forecasting
Time-series forecasting plays an important role in many real-world scena...
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04/06/2022
Spatio-Temporal Dynamic Graph Relation Learning for Urban Metro Flow Prediction
Urban metro flow prediction is of great value for metro operation schedu...
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02/25/2022
Spatio-Temporal Latent Graph Structure Learning for Traffic Forecasting
Accurate traffic forecasting, the foundation of intelligent transportati...
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02/23/2022
A Differential Attention Fusion Model Based on Transformer for Time Series Forecasting
Time series forecasting is widely used in the fields of equipment life c...
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12/18/2020
Fairness and Accuracy in Federated Learning
In the federated learning setting, multiple clients jointly train a mode...
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08/26/2019
Urban flows prediction from spatial-temporal data using machine learning: A survey
Urban spatial-temporal flows prediction is of great importance to traffi...
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12/12/2018
Deep Air Quality Forecasting Using Hybrid Deep Learning Framework
Air quality forecasting has been regarded as the key problem of air poll...
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03/06/2018
