Researchers unveil time series deep learning technique for optimal performance in AI models

A team of researchers has unveiled a time series machine learning technique designed to address data drift challenges. This innovative approach, led by Professor Sungil Kim and Professor Dongyoung Lim from the Department of Industrial Engineering and the Artificial Intelligence Graduate School at UNIST, effectively handles irregular sampling intervals and missing values in real-world time series data, offering a robust solution for ensuring optimal performance in artificial intelligence (AI) models.

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