Deep learning for cosmology: Challenges and opportunities

Speaker: 
Siamak Ravanbakhs (UBC Computer Science)
Event Date and Time: 
Mon, 2018-03-26 15:00 - 16:15
Location: 
Hennings 318
Local Contact: 
Jaymie Matthews
Intended Audience: 
Graduate
A primary goal of modern cosmology is to map complex large-scale observations to simple theories. This contrast of scale between theory and data inevitably necessitates a computational approach. This computation may involve a compressive analysis of observational data, massive simulations, active exploration, or a search for rare events. In this talk, I will argue that recent advances in machine learning, and in particular deep learning can significantly impact the current practice in all of these fronts. I will review several of our past and ongoing collaborations and identify challenges along with exciting opportunities for interdisciplinary research.
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