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Multi-Term Fourier Graph Neural Network with Sample Relationship Learning for Enhanced Remaining Useful Life Prediction

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benchmarks

arXiv Machine Learning

Sep 23

Multi-Term Fourier Graph Neural Network with Sample Relationship Learning for Enhanced Remaining Useful Life Prediction

arXiv:2609.25179v1 Announce Type: new Abstract: Predicting the remaining useful life (RUL) is essential for effective predictive maintenance. Spatio-Temporal Graph Neural Networks (ST-GNNs), which ca...

By Ya Song, Laurens Bliek, Yaoxin Wu, Yingqian Zhang

benchmarks

arXiv AI

Jun 15

MP3: Multi-Period Pattern Pre-training for Spatio-Temporal Forecasting

arXiv:2606. 13119v2 Announce Type: replace-cross Abstract: Spatio-Temporal forecasting is crucial in diverse fields, such as transportation, climate, and energy.

By Lilan Peng, Yandi Liu, Qingren Yao, Chongshou Li, Tianrui Li

llms

arXiv AI

Jun 12

MP3: Multi-Period Pattern Pre-training forSpatio-Temporal Forecasting

arXiv:2606. 13119v1 Announce Type: cross Abstract: Spatio-Temporal forecasting is crucial in diverse fields, such as transportation, climate, and energy.

By Lilan Peng, Yandi Liu, Qingren Yao, Chongshou Li, Tianrui Li

llms

arXiv Machine Learning

Aug 24

A Critical Audit of Spatiotemporal Forecasting Benchmark Datasets and Baselines

arXiv:2608.20980v1 Announce Type: new Abstract: Graph neural networks (GNNs) are routinely employed for short-range forecasting on multivariate time series with a spatial graph structure. Despite the...

By Kenneth Martin, Simon Heilig, Asja Fischer, Michel F. C. Haddad, Adam M. Sykulski, Moshe Eliasof

benchmarks safety

arXiv Machine Learning

Aug 21

Multi-Modal Graph Interaction for Multi-Graph Convolution Network in Urban Spatiotemporal Forecasting

arXiv:1905. 11395v2 Announce Type: replace Abstract: Graph convolution network based approaches have been recently used to model region-wise relationships in region-level prediction problems in urban computing.

By Lingyu Zhang, Xu Geng, Zhiwei Qin, Hongjun Wang, Xiao Wang, Ying Zhang, Jian Liang, Guobin Wu, Xuan Song, Yunhai Wang

multimodal safety

arXiv Machine Learning

Aug 12

GARLIC: Graph Attention-based Relational Learning of Multivariate Time Series in Intensive Care

arXiv:2608. 10969v1 Announce Type: new Abstract: Healthcare data, such as Intensive Care Unit (ICU) records, comprise heterogeneous multivariate time series sampled at irregular intervals with pervasive missingness.

By Ruirui Wang, Yanke Li, Manuel G\"unther, Diego Paez-Granados

benchmarks

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Multi-Term Fourier Graph Neural Network with Sample Relationship Learning for Enhanced Remaining Useful Life Prediction

MP3: Multi-Period Pattern Pre-training for Spatio-Temporal Forecasting

MP3: Multi-Period Pattern Pre-training forSpatio-Temporal Forecasting

A Critical Audit of Spatiotemporal Forecasting Benchmark Datasets and Baselines

Multi-Modal Graph Interaction for Multi-Graph Convolution Network in Urban Spatiotemporal Forecasting

GARLIC: Graph Attention-based Relational Learning of Multivariate Time Series in Intensive Care