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Automated event detection in the sequences is an important aspect of temporaldata analytics. The events can be in the form of peaks, changes in datadistribution, changes of spectral characteristics etc. In this work, we proposea Soft-Attention Convolutional Neural Network (CNN) based approach for rareevent detection in sequences. For the purpose of demonstration, we experimentwith well logs where we aim to detect events depicting the changes in thegeological layers (a.k.a. well tops/markers). Well logs (single ormultivariate) are inputted to a soft attention CNN and a model is trained tolocate the marker position. Attention mechanism enables the machine torelatively scale the relevant log features for the task. Experimental resultsshow that our approach is able to locate the rare events with high precision.

Soft Attention Convolutional Neural Networks for Rare Event Detection in Sequences