March 11, 2021
3:00PM
-
4:00PM
ONLINE: Zoom Webinar
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2021-03-11 15:00:00
2021-03-11 16:00:00
Astronomy Colloquium - Joe Antognini
An Astronomer Does Machine Learning
In the past decade, deep learning has revolutionized machine perception and gone from being a little-known niche field to vastly outperforming other algorithms at tasks as diverse as image classification, text-to-speech production, and natural language processing. The tremendous success of deep learning has led to billions of dollars of investment in the development of these models in industry. Nevertheless, foundational open questions remain in the field and I argue these are inherently scientific in nature. I will provide a brief introduction to machine learning for astronomers and discuss what I see are the outstanding open questions, along with a particular application of these techniques to the problem of denoising in hearing aids.
Speaker: Joe Antognini (Whisper AI - Private Industry)
ONLINE: Zoom Webinar
OSU ASC Drupal 8
ascwebservices@osu.edu
America/New_York
public
Date Range
2021-03-11 15:00:00
2021-03-11 16:00:00
Astronomy Colloquium - Joe Antognini
An Astronomer Does Machine Learning
In the past decade, deep learning has revolutionized machine perception and gone from being a little-known niche field to vastly outperforming other algorithms at tasks as diverse as image classification, text-to-speech production, and natural language processing. The tremendous success of deep learning has led to billions of dollars of investment in the development of these models in industry. Nevertheless, foundational open questions remain in the field and I argue these are inherently scientific in nature. I will provide a brief introduction to machine learning for astronomers and discuss what I see are the outstanding open questions, along with a particular application of these techniques to the problem of denoising in hearing aids.
Speaker: Joe Antognini (Whisper AI - Private Industry)
ONLINE: Zoom Webinar
America/New_York
public
An Astronomer Does Machine Learning
In the past decade, deep learning has revolutionized machine perception and gone from being a little-known niche field to vastly outperforming other algorithms at tasks as diverse as image classification, text-to-speech production, and natural language processing. The tremendous success of deep learning has led to billions of dollars of investment in the development of these models in industry. Nevertheless, foundational open questions remain in the field and I argue these are inherently scientific in nature. I will provide a brief introduction to machine learning for astronomers and discuss what I see are the outstanding open questions, along with a particular application of these techniques to the problem of denoising in hearing aids.
