2 citations · 2 across the 5 of their papers we have counts for
6 papers
The Cross-Survey Decade: A Call to Action
Gioia Rau, Robert Benjamin, Federica Bianco +24
By 2027, three flagship wide-field surveys will be operating simultaneously from ground and space, observing overlapping sky and representing more than $6 billion in US and Europea…
DiscoverPhysics: Benchmarking LLMs for Out-of-the-Box Scientific Thinking
Matt L. Wiemann, Lindsay M. Smith, Peter Melchior +4
Frontier LLMs now perform strongly across a wide range of physics evaluations, but it is hard to disentangle genuine reasoning from recall of established science. We introduce Disc…
Opportunities in AI/ML for the Rubin LSST Dark Energy Science Collaboration
LSST Dark Energy Science Collaboration, Eric Aubourg, Camille Avestruz +63
The Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) will produce unprecedented volumes of heterogeneous astronomical data (images, catalogs, and alerts) that cha…
The Optical and Infrared Are Connected
Christian K. Jespersen, Peter Melchior, David N. Spergel +3
Galaxies are often modelled as composites of separable components with distinct spectral signatures, implying that different wavelength ranges are only weakly correlated. They are…
The Multimodal Universe: Enabling Large-Scale Machine Learning with 100TB of Astronomical Scientific Data
The Multimodal Universe Collaboration, Jeroen Audenaert, Micah Bowles +26
We present the MULTIMODAL UNIVERSE, a large-scale multimodal dataset of scientific astronomical data, compiled specifically to facilitate machine learning research. Overall, the MU…
Multiscale Feature Attribution for Outliers
Jeff Shen, Peter Melchior
Machine learning techniques can automatically identify outliers in massive datasets, much faster and more reproducible than human inspection ever could. But finding such outliers i…