2 citations · 2 across the 3 of their papers we have counts for
3 papers
astro-ph.IM2024
Preliminary Report on Mantis Shrimp: a Multi-Survey Computer Vision Photometric Redshift Model
Andrew Engel, Gautham Narayan, Nell Byler
The availability of large, public, multi-modal astronomical datasets presents an opportunity to execute novel research that straddles the line between science of AI and science of…
astro-ph.IM2023★ 2 cited
Evaluating Physically Motivated Loss Functions for Photometric Redshift Estimation
Andrew Engel, Jan Strube
Physical constraints have been suggested to make neural network models more generalizable, act scientifically plausible, and be more data-efficient over unconstrained baselines. In…
cs.LG2023
Exploring Learned Representations of Neural Networks with Principal Component Analysis
Amit Harlev, Andrew Engel, Panos Stinis +1
Understanding feature representation for deep neural networks (DNNs) remains an open question within the general field of explainable AI. We use principal component analysis (PCA)…