GAN for Time Series Data Augmentation in Astronomy

Pavlos Protopapas present a solution for imbalanced real-world datasets and time series tasks using a Conditional Wasserstein GAN.
Written on 
Jan 5, 2023
in 
Talks

GAN for Time Series Data Augmentation in Astronomy

Pavlos Protopapas present a solution for imbalanced real-world datasets and time series tasks using a Conditional Wasserstein GAN.
Written on 
Jan 5, 2023
in 
Talks

GAN for Time Series Data Augmentation in Astronomy

Pavlos Protopapas present a solution for imbalanced real-world datasets and time series tasks using a Conditional Wasserstein GAN.
Written on 
Jan 5, 2023
in 
Talks

GAN for Time Series Data Augmentation in Astronomy

Pavlos Protopapas present a solution for imbalanced real-world datasets and time series tasks using a Conditional Wasserstein GAN.
Written on 
Jan 5, 2023
in 
Talks
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Written on 
Jan 5, 2023
in 
Talks

Pavlos is the Scientific Program Director, Institute for Applied Computational Science (IACS) at Harvard University, and leads the Data Science Masters Program at Harvard. Pavlos has had a distinguished career as a scientist and data science educator, and to day teaches the CS109 series for basic and advanced data science at Harvard, as well as the capstone course (industry-sponsored data science projects) for the IACS Masters Program. Pavlos has a Ph.D in theoretical physics from the University of Pennsylvania. Pavlos research has since branched into the use of machine learning and AI in astronomy, and computer science. He is excited to be a partner of univ.ai, helping steer us to world-class excellence in AI Research and education, this summer and beyond, asuniv.ai sets sail on its mission.

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