Generative Adversarial Networks recover features in astrophysical images of galaxies beyond the deconvolution limit. - Kevin Schawinski; Ce Zhang 001; Hantian Zhang; Lucas Fowler; Gokula Krishnan Santhanam (CoRR, 2017)

Using transfer learning to detect galaxy mergers. - Sandro Ackermann; Kevin Schawinski; Ce Zhang 001; Anna K. Weigel; M. Dennis Turp (CoRR, 2018)

Exploring galaxy evolution with generative models. - Kevin Schawinski; M. Dennis Turp; Ce Zhang 001 (CoRR, 2018)

Continuous Integration of Machine Learning Models with ease.ml/ci: Towards a Rigorous Yet Practical Treatment. - Cédric Renggli; Bojan Karlas; Bolin Ding; Feng Liu; Kevin Schawinski; Wentao Wu 001; Ce Zhang 001 (SysML, 2019)

Ease.ml/ci and Ease.ml/meter in Action: Towards Data Management for Statistical Generalization. - Cédric Renggli; Frances Ann Hubis; Bojan Karlas; Kevin Schawinski; Wentao Wu 001; Ce Zhang 001 (Proc. VLDB Endow., 2019)

Ease.ML: A Lifecycle Management System for Machine Learning. - Leonel Aguilar Melgar; David Dao; Shaoduo Gan; Nezihe Merve Gürel; Nora Hollenstein; Jiawei Jiang 001; Bojan Karlas; Thomas Lemmin; Tian Li 005; Yang Li 106; Susie Xi Rao; Johannes Rausch; et al. (CIDR, 2021)

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 003; Ryan Ofman; Tonima Tasnim Ananna; Connor Auge; Nico Cappelluti; Meredith C. Powell; David B. Sanders; Kevin Schawinski; Dominic Stark; Grant R. Tremblay (CoRR, 2022)

AstroLLaMA: Towards Specialized Foundation Models in Astronomy. - Tuan Dung Nguyen; Yuan-Sen Ting; Ioana Ciuca; Charlie O'Neill; Zechang Sun; Maja Jablonska; Sandor Kruk; Ernest Perkowski; Jack W. Miller; Jason Li; Josh Peek; Kartheik Iyer; et al. (CoRR, 2023)

AstroLLaMA-Chat: Scaling AstroLLaMA with Conversational and Diverse Datasets. - Ernest Perkowski; Rui Pan 002; Tuan Dung Nguyen; Yuan-Sen Ting; Sandor Kruk; Tong Zhang 001; Charlie O'Neill; Maja Jablonska; Zechang Sun; Michael J. Smith 013; Huiling Liu; Kevin Schawinski; et al. (CoRR, 2024)

pathfinder: A Semantic Framework for Literature Review and Knowledge Discovery in Astronomy. - Kartheik Iyer; Mikaeel Yunus; Charles O'Neill; Christine Ye; Alina Hyk; Kiera McCormick; Ioana Ciuca; John F. Wu; Alberto Accomazzi; Simone Astarita; Rishabh Chakrabarty; Jesse Cranney; et al. (CoRR, 2024)

Automatic Machine Learning Framework to Study Morphological Parameters of AGN Host Galaxies within z < 1.4 in the Hyper Supreme-Cam Wide Survey. - Chuan Tian; C. Megan Urry; Aritra Ghosh 003; Daisuke Nagai; Tonima Tasnim Ananna; Meredith C. Powell; Connor Auge; Aayush Mishra; David B. Sanders; Nico Cappelluti; Kevin Schawinski (CoRR, 2025)

A Survey on Hypothesis Generation for Scientific Discovery in the Era of Large Language Models. - Atilla Kaan Alkan; Shashwat Sourav; Maja Jablonska; Simone Astarita; Rishabh Chakrabarty; Nikhil Garuda; Pranav Khetarpal; Maciej Pióro; Dimitrios Tanoglidis; Kartheik Iyer; Mugdha Polimera; Michael J. Smith 013; et al. (CoRR, 2025)

Sparks of Science: Hypothesis Generation Using Structured Paper Data. - Charles O'Neill; Tirthankar Ghosal; Roberta Raileanu; Mike Walmsley; Thang D. Bui; Kevin Schawinski; Ioana Ciuca (CoRR, 2025)