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cs.LG2021
Pattern Sampling for Shapelet-based Time Series Classification
Atif Raza, Stefan Kramer
Subsequence-based time series classification algorithms provide accurate and interpretable models, but training these models is extremely computation intensive. The asymptotic time…
cs.LG2021
Deep Neural Networks to Recover Unknown Physical Parameters from Oscillating Time Series
Antoine Garcon, Julian Vexler, Dmitry Budker +1
Deep neural networks (DNNs) are widely used in pattern-recognition tasks for which a human comprehensible, quantitative description of the data-generating process, e.g., in the for…