John F. Wu

According to our database, John F. Wu authored at least 10 papers between 2020 and 2025.

Collaborative distances:

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

2025

From Queries to Criteria: Understanding How Astronomers Evaluate LLMs.

Alina Hyk, Kiera McCormick, Mian Zhong, Ioana Ciuca, Sanjib Sharma, John F. Wu, Joshua E. G. Peek, Kartheik Iyer, Ziang Xiao, Anjalie Field

CoRR, July, 2025

Insights on Galaxy Evolution from Interpretable Sparse Feature Networks.

John F. Wu

CoRR, January, 2025

2024

Deep learning cosmic ray transport from density maps of simulated, turbulent gas.

Chad Bustard, John F. Wu

Mach. Learn. Sci. Technol., March, 2024

Estimating Dark Matter Halo Masses in Simulated Galaxy Clusters with Graph Neural Networks.

Nikhil Garuda, John F. Wu, Dylan Nelson, Annalisa Pillepich

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, Anjalie Field, Tirthankar Ghosal, Michele Ginolfi, Marc Huertas-Company, Maja Jablonska, Sandor Kruk, Huiling Liu, Gabriel Marchidan, Rohit Mistry, Jill P. Naiman, Joshua E. G. Peek, Mugdha Polimera, Sergio J. Rodríguez Méndez, Kevin Schawinski, Sanjib Sharma, Michael J. Smith, Yuan-Sen Ting, Mike Walmsley

CoRR, 2024

Disentangling Dense Embeddings with Sparse Autoencoders.

Charles O'Neill, Christine Ye, Kartheik Iyer, John F. Wu

CoRR, 2024

Designing an Evaluation Framework for Large Language Models in Astronomy Research.

John F. Wu, Alina Hyk, Kiera McCormick, Christine Ye, Simone Astarita, Elina Baral, Jo Ciuca, Jesse Cranney, Anjalie Field, Kartheik Iyer, Philipp Koehn, Jenn Kotler, Sandor Kruk, Michelle Ntampaka, Charles O'Neill, Joshua E. G. Peek, Sanjib Sharma, Mikaeel Yunus

CoRR, 2024

The Multimodal Universe: Enabling Large-Scale Machine Learning with 100 TB of Astronomical Scientific Data.

Eirini Angeloudi, Jeroen Audenaert, Micah Bowles, Benjamin M. Boyd, David Chemaly, Brian Cherinka, Ioana Ciuca, Miles D. Cranmer, Aaron Do, Matthew Grayling, Erin E. Hayes, Tom Hehir, Shirley Ho, Marc Huertas-Company, Kartheik Iyer, Maja Jablonska, François Lanusse, Henry Leung, Kaisey Mandel, Rafael Martínez-Galarza, Peter Melchior, Lucas Meyer, Liam Holden Parker, Helen Qu, Jeff Shen, Michael J. Smith, Connor Stone, Mike Walmsley, John F. Wu

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

2023

Constructing Impactful Machine Learning Research for Astronomy: Best Practices for Researchers and Reviewers.

Daniela Huppenkothen, Michelle Ntampaka, M. Ho, M. Fouesneau, Brian Nord, Joshua E. G. Peek, Mike Walmsley, John F. Wu, Camille Avestruz, T. Buck, M. Brescia, D. P. Finkbeiner, Andy D. Goulding, Tomasz Kacprzak, Peter Melchior, M. Pasquato, Nesar Ramachandra, Yuan-Sen Ting, G. van de Ven, S. Villar, V. A. Villar, E. Zinger

CoRR, 2023

2020

Predicting galaxy spectra from images with hybrid convolutional neural networks.

John F. Wu, Joshua E. G. Peek

CoRR, 2020