1.5k citations · 2.9k across the 28 of their papers we have counts for
4 papers · 1 filter
Unsupervised in-distribution anomaly detection of new physics through conditional density estimation
George Stein, Uros Seljak, Biwei Dai
Anomaly detection is a key application of machine learning, but is generally focused on the detection of outlying samples in the low probability density regions of data. Here we in…
Self-Supervised Representation Learning for Astronomical Images
Md Abul Hayat, George Stein, Peter Harrington +2
Sky surveys are the largest data generators in astronomy, making automated tools for extracting meaningful scientific information an absolute necessity. We show that, without the n…
Nonlinear 3D Cosmic Web Simulation with Heavy-Tailed Generative Adversarial Networks
Richard M. Feder, Philippe Berger, George Stein
Fast and accurate simulations of the non-linear evolution of the cosmic density field are a major component of many cosmological analyses, but the computational time and storage re…
The Websky Extragalactic CMB Simulations
George Stein, Marcelo A. Alvarez, J. Richard Bond +2
We present a new pipeline for the efficient generation of synthetic observations of the extragalactic microwave sky, tailored to large ground-based CMB experiments such as the Simo…