455 citations · 763 across the 16 of their papers we have counts for
5 papers · 1 filter
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…
HyPhy: Deep Generative Conditional Posterior Mapping of Hydrodynamical Physics
Benjamin Horowitz, Max Dornfest, Zarija Lukić +1
Generating large volume hydrodynamical simulations for cosmological observables is a computationally demanding task necessary for next generation observations. In this work, we con…
Fast, high-fidelity Lyman forests with convolutional neural networks
Peter Harrington, Mustafa Mustafa, Max Dornfest +2
Full-physics cosmological simulations are powerful tools for studying the formation and evolution of structure in the universe but require extreme computational resources. Here, we…
Estimating Galactic Distances From Images Using Self-supervised Representation Learning
Md Abul Hayat, Peter Harrington, George Stein +2
We use a contrastive self-supervised learning framework to estimate distances to galaxies from their photometric images. We incorporate data augmentations from computer vision as w…