5–6 Jun 2017
Fermilab, Wilson Hall
US/Central timezone

AstroEncoder: Applications of Deep Learning to Cosmological Data

5 Jun 2017, 14:00
15m
One West (Fermilab, Wilson Hall)

One West

Fermilab, Wilson Hall

Oral Presentation Dark Matter and Astrophysics

Speaker

Dr Brian Nord (Fermilab)

Description

Current and future cosmology surveys will provide data sets unprecedented in size and precision with which to measure dark energy, dark matter and the early universe through probes like strong gravitational lensing, supernovae, and the cosmic microwave background. First, we’ll discuss the challenges posed by astronomically big and complex data, and the potential for machine learning. Then, I will present a variety of successful applications of deep learning techniques to astrophysical and cosmological data, including classification, measurement, and simulation.

Primary author

Dr Brian Nord (Fermilab)

Co-author

Dr Irshad Mohammed (Fermilab)

Presentation materials