Kevin Schawinski

According to our database, Kevin Schawinski authored at least 9 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

AstroLLaMA-Chat: Scaling AstroLLaMA with Conversational and Diverse Datasets.

Ernest Perkowski, Rui Pan, Tuan Dung Nguyen, Yuan-Sen Ting, Sandor Kruk, Tong Zhang, Charlie O'Neill, Maja Jablonska, Zechang Sun, Michael J. Smith, Huiling Liu, Kevin Schawinski, Kartheik Iyer, Ioana Ciuca, UniverseTBD

CoRR, 2024

2023

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, Tomasz Rózanski, Pranav Khetarpal, Sharaf Zaman, David Brodrick, Sergio J. Rodríguez Méndez, Thang Bui, Alyssa Goodman, Alberto Accomazzi, Jill P. Naiman, Jesse Cranney, Kevin Schawinski, UniverseTBD

CoRR, 2023

2022

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

CoRR, 2022

2021

Ease.ML: A Lifecycle Management System for Machine Learning.

Leonel Aguilar Melgar, David Dao, Shaoduo Gan, Nezihe Merve Gürel, Nora Hollenstein, Jiawei Jiang, Bojan Karlas, Thomas Lemmin, Tian Li, Yang Li, Susie Xi Rao, Johannes Rausch, Cédric Renggli, Luka Rimanic, Maurice Weber, Shuai Zhang, Zhikuan Zhao, Kevin Schawinski, Wentao Wu, Ce Zhang

Proceedings of the 11th Conference on Innovative Data Systems Research, 2021

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, Ce Zhang

Proc. VLDB Endow., 2019

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, Ce Zhang

Proceedings of Machine Learning and Systems 2019, 2019

2018

Exploring galaxy evolution with generative models.

Kevin Schawinski, M. Dennis Turp, Ce Zhang

CoRR, 2018

Using transfer learning to detect galaxy mergers.

Sandro Ackermann, Kevin Schawinski, Ce Zhang, Anna K. Weigel, M. Dennis Turp

CoRR, 2018

2017

Generative Adversarial Networks recover features in astrophysical images of galaxies beyond the deconvolution limit.

Kevin Schawinski, Ce Zhang, Hantian Zhang, Lucas Fowler, Gokula Krishnan Santhanam

CoRR, 2017