1.5k citations · 2.9k across the 28 of their papers we have counts for
28 papers
Exposing flaws of generative model evaluation metrics and their unfair treatment of diffusion models
George Stein, Jesse C. Cresswell, Rasa Hosseinzadeh +7
We systematically study a wide variety of generative models spanning semantically-diverse image datasets to understand and improve the feature extractors and metrics used to evalua…
Exploring the Non-Gaussianity of the Cosmic Infrared Background and Its Weak Gravitational Lensing
Jaemyoung Lee, J. Richard Bond, Pavel Motloch +2
Gravitational lensing deflects the paths of photons, altering the statistics of cosmic backgrounds and distorting their information content. We take the Cosmic Infrared Background…
A Probabilistic Autoencoder for Type Ia Supernovae Spectral Time Series
George Stein, Uros Seljak, Vanessa Bohm +37
We construct a physically-parameterized probabilistic autoencoder (PAE) to learn the intrinsic diversity of type Ia supernovae (SNe Ia) from a sparse set of spectral time series. T…
Self-supervised similarity search for large scientific datasets
George Stein, Peter Harrington, Jacqueline Blaum +2
We present the use of self-supervised learning to explore and exploit large unlabeled datasets. Focusing on 42 million galaxy images from the latest data release of the Dark Energy…
Mining for Strong Gravitational Lenses with Self-supervised Learning
George Stein, Jacqueline Blaum, Peter Harrington +2
We employ self-supervised representation learning to distill information from 76 million galaxy images from the Dark Energy Spectroscopic Instrument Legacy Imaging Surveys' Data Re…
Superclustering with the Atacama Cosmology Telescope and Dark Energy Survey: I. Evidence for thermal energy anisotropy using oriented stacking
M. Lokken, R. Hložek, A. van Engelen +104
The cosmic web contains filamentary structure on a wide range of scales. On the largest scales, superclustering aligns multiple galaxy clusters along inter-cluster bridges, visible…