10 citations · 12 across the 2 of their papers we have counts for
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astro-ph.CO2019
Differentiable Strong Lensing: Uniting Gravity and Neural Nets through Differentiable Probabilistic Programming
Marco Chianese, Adam Coogan, Paul Hofma +2
Since upcoming telescopes will observe thousands of strong lensing systems, creating fully-automated analysis pipelines for these images becomes increasingly important. In this wor…
cs.LG2019
Constraining the Parameters of High-Dimensional Models with Active Learning
Sascha Caron, Tom Heskes, Sydney Otten +1
Constraining the parameters of physical models with parameters is a widespread problem in fields like particle physics and astronomy. The generation of data to explore this…
hep-ph2019
Event Generation and Statistical Sampling for Physics with Deep Generative Models and a Density Information Buffer
Sydney Otten, Sascha Caron, Wieske de Swart +6
We present a study for the generation of events from a physical process with deep generative models. The simulation of physical processes requires not only the production of physic…