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Big data tools for physics and astronomy

Monday 19 June 2017 - 09:00
Other Institutes

        : Sessions
    /     : Talks
        : Breaks
19 Jun 2017
AM
09:00 Watch this space: emerging trends and techniques that could transform physics and astronomy - Kyle Stuart Cranmer (New York University (US))  
09:45 Inter-experimental Machine Learning at the LHC - Dr Sergei Gleyzer (University of Florida (US))  
10:15 Large Scale Machine Learning in Astronomy - Gieseke Fabian  
11:05 GRID Processing of LOFAR spectroscopic and imaging surveys - Natalie Danezi (SurfSara)  
11:35 HPC Processing and Deep Learning Techniques for Classifying Radio Bursts - Joeri van Leeuwen  
PM
12:05 Collaborative machine learning for science with OpenML - Prof. Joaquin Vanschoren (TU Eindhoven)  
14:00 Amsterdam Data Science - Maarten de Rijke  
14:30 eScience - Wilco Hazeleger  
15:00 SurfSara - Maithili Kalamkar  
16:00 Determining the origin of the Galactic Center excess using convolutional neural networks - Mr Hendriks Luc  
16:15 Scaling up in complexity - Zahari Dimitrov Kassabov Zaharieva (University of Turin)  
16:30 Good fits of gamma-ray data with high-dimensional modelling - Dr Emma Storm (UvA)  
16:45 Generalizing LHC limits on Supersymmetry with Machine Learning - Mr Bob Stienen (IMAPP, Radboud University Nijmegen)  
17:00 Wrap-up and next steps - Juan Rojo (VU Amsterdam and Nikhef)  
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