196 citations · 388 across the 14 of their papers we have counts for
16 papers
Distilling Graph Geometry: Knowledge Gap from GNNs to MLPs
Zhewei Chen, Hao Zhu, Jiaojiao Jiang +1
GNN-to-MLP distillation aims to retain the predictive accuracy of a message-passing teacher while deploying a graph-free MLP at inference. Existing methods mainly transfer node-wis…
Feature-driven anomaly flagging in obscured active galactic nucleus light curves with autoencoders
Natale De Bonis, Demetra De Cicco, Stefano Cavuoti +5
Active galactic nuclei (AGN) are among the most complex classes of astrophysical objects, displaying a wide range of variability and observational properties. Identifying unusual A…
VAR-PZnn: A machine-learning framework for AGN photometric redshifts using color and variability-based features
S. Satheesh-Sheeba, P. Sánchez-Sáez, R. J. Assef +39
Photometric redshift estimation for active galactic nuclei (AGNs) remains a fundamental challenge for current and upcoming large-scale photometric surveys. Traditional spectral ene…
AGILE: an end-to-end Rubin-LSST simulation of AGNs, galaxies, and stars I. Software description and first data release
A. Viitanen, A. Bongiorno, I. Saccheo +37
Contemporary large-scale surveys such as the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) and Euclid present an unprecedented discovery potential for studying A…
AGN in massive galaxies identified via optical broadband variability: lessons from VST-COSMOS for future LSST science
B. Bichang'a, D. De Cicco, S. Kaviraj +4
We study the properties of 56 massive (M > 10 M) galaxies at that host AGN, detected via their broadband optical variability in the VST-COSMOS…
Scalable and Robust Multiband Modeling of AGN Light Curves in Rubin-LSST
Weixiang Yu, John J. Ruan, Colin J. Burke +22
The Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) will monitor tens of millions of active galactic nuclei (AGNs) for a period of 10 years with an average caden…