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cs.LG2025
An Unsupervised Time Series Anomaly Detection Approach for Efficient Online Process Monitoring of Additive Manufacturing
Frida Cantu, Salomon Ibarra, Arturo Gonzales +3
Online sensing plays an important role in advancing modern manufacturing. The real-time sensor signals, which can be stored as high-resolution time series data, contain rich inform…
cs.LG2024★ 4 cited
COSCO: A Sharpness-Aware Training Framework for Few-shot Multivariate Time Series Classification
Jesus Barreda, Ashley Gomez, Ruben Puga +2
Multivariate time series classification is an important task with widespread domains of applications. Recently, deep neural networks (DNN) have achieved state-of-the-art performanc…