Unified training of universal time series forecasting transformers

• Main Authors: WOO, Gerald, LIU, Chenghao, KUMAR, Akshat, XIONG, Caiming, SAVARESE, Silvio, SAHOO, Doyen
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2024
• Subjects: Time series forecast; Deep learning; Time series transformer; Artificial Intelligence and Robotics
• Online Access: https://ink.library.smu.edu.sg/sis_research/9906; https://ink.library.smu.edu.sg/context/sis_research/article/10906/viewcontent/2402.02592v2.pdf
• Institution: Singapore Management University

Deep learning for time series forecasting has traditionally operated within a one-model-per-dataset framework, limiting its potential to leverage the game-changing impact of large pre-trained models. The concept of universal forecasting, emerging from pre-training on a vast collection of time series...