Ryan Ofman

most citedGaMPEN: A Machine Learning Framework for Estimating Bayesian Posteriors of Galaxy Morphological Parameters

13 citations · 18 across the 3 of their papers we have counts for

collaborators

3 papers

cs.LG2025★ 1 cited

What You Read Isn't What You Hear: Linguistic Sensitivity in Deepfake Speech Detection

Binh Nguyen, Shuji Shi, Ryan Ofman +1

Recent advances in text-to-speech technologies have enabled realistic voice generation, fueling audio-based deepfake attacks such as fraud and impersonation. While audio anti-spoof…

astro-ph.GA2022★ 4 cited

Using Machine Learning to Determine Morphologies of $z < 1$ AGN Host Galaxies in the Hyper Suprime-Cam Wide Survey

Chuan Tian, C. Megan Urry, Aritra Ghosh +9

We present a machine-learning framework to accurately characterize morphologies of Active Galactic Nucleus (AGN) host galaxies within $z < 1$ . We first use PSFGAN to decouple host ga…

astro-ph.GA2022★ 13 cited

GaMPEN: A Machine Learning Framework for Estimating Bayesian Posteriors of Galaxy Morphological Parameters

Aritra Ghosh, C. Megan Urry, Amrit Rau +11

We introduce a novel machine learning framework for estimating the Bayesian posteriors of morphological parameters for arbitrarily large numbers of galaxies. The Galaxy Morphology…

What You Read Isn't What You Hear: Linguistic Sensitivity in Deepfake Speech Detection

Using Machine Learning to Determine Morphologies of z<1 AGN Host Galaxies in the Hyper Suprime-Cam Wide Survey

GaMPEN: A Machine Learning Framework for Estimating Bayesian Posteriors of Galaxy Morphological Parameters

Using Machine Learning to Determine Morphologies of $z < 1$ AGN Host Galaxies in the Hyper Suprime-Cam Wide Survey