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Frontiers of Foundation Models for Time Series

Offered By: Association for Computing Machinery (ACM) via YouTube

Tags

Time Series Analysis Courses Machine Learning Courses Deep Learning Courses Distributed Systems Courses Climate Science Courses Foundation Models Courses Interpretability Courses

Course Description

Overview

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Explore the frontiers of foundation models for time series in this keynote talk from the Large Language Model Day at KDD2024. Delve into the recent advancements in deep learning that have propelled research in time series modeling and analysis. Discover the new challenges posed by practical applications of time series in scientific domains, including multi-resolution, multimodal data, missing values, distributedness, and interpretability. Learn about potential pathways towards developing foundation models specifically designed for time series data and gain insights into future research directions in this field. Presented by Yan Liu, a Professor in the Computer Science Department and Director of the Machine Learning Center at the University of Southern California, this 36-minute talk draws from her extensive experience in machine learning applications across climate science, healthcare, and sustainability.

Syllabus

KDD2024 - Frontiers of Foundation Models for Time Series


Taught by

Association for Computing Machinery (ACM)

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