Mike Walmsley

According to our database, Mike Walmsley authored at least 23 papers between 2019 and 2026.

Collaborative distances:

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

2026

Euclid Quick Data Release (Q1). AgileLens: A scalable CNN-based pipeline for strong gravitational lens identification.

X. Xu, R. Chen, T. Li, A. R. Cooray, Stefan Schuldt, J. A. Acevedo Barroso, D. Stern, Douglas Scott, Massimo Meneghetti, G. Despali, J. Chopra, Y. Cao, M. Cheng, J. Buda, J. Zhang, J. Furumizo, R. Valencia, Z. Jiang, C. Tortora, N. E. P. Lines, T. E. Collett, Sotiria Fotopoulou, Aymeric Galan, A. Manjón-García, R. Gavazzi, L. Iwamoto, S. Kruk, Martin Millon, P. Nugent, C. Saulder, Dominique Sluse, J. Wilde, Mike Walmsley, Frédéric Courbin, R. B. Metcalf, Bruno Altieri, Adam Amara, S. Andreon, N. Auricchio, C. Baccigalupi, Marco Baldi, A. Balestra, S. Bardelli, P. Battaglia, R. Bender, Andrea Biviano, E. Branchini, Massimo Brescia, S. Camera, Vito Capobianco, C. Carbone, Vincenzo F. Cardone, Jorge Carretero, S. Casas, M. Castellano, G. Castignani, Stefano Cavuoti, Andrea Cimatti, C. Colodro-Conde, Giuseppe Congedo, Christopher J. Conselice, Luca Conversi, Y. Copin, H. M. Courtois, Mark Cropper, A. Da Silva, Hubert Degaudenzi, G. De Lucia, C. Dolding, H. Dole, Florian Dubath, X. Dupac, S. Dusini, S. Escoffier, M. Farina, R. Farinelli, S. Farrens, S. Ferriol, F. Finelli, Pablo Fosalba, Marco Frailis, Enrico Franceschi, M. Fumana, S. Galeotta, K. George, W. Gillard, B. Gillis, Carlo Giocoli, P. Gómez-Alvarez, J. Gracia-Carpio, A. Grazian, F. Grupp, S. V. H. Haugan, W. Holmes, F. Hormuth, A. Hornstrup, K. Jahnke, M. Jhabvala, et al.

CoRR, April, 2026

Spatio-Spectroscopic Representation Learning using Unsupervised Convolutional Long-Short Term Memory Networks.

Kameswara Bharadwaj Mantha, Lucy Fortson, Ramanakumar Sankar, Claudia Scarlata, Chris J. Lintott, Sandor Kruk, Mike Walmsley, Hugh Dickinson, Karen Masters, Brooke Simmons, Rebecca J. Smethurst

CoRR, February, 2026

2025

Pre-training vision models for the classification of alerts from wide-field time-domain surveys.

Nabeel Rehemtulla, Adam A. Miller, Mike Walmsley, Ved G. Shah, Theophile Jegou du Laz, Michael W. Coughlin, Argyro Sasli, Joshua Bloom, Christoffer Fremling, Matthew J. Graham, Steven L. Groom, David Hale, Ashish A. Mahabal, Daniel A. Perley, Josiah Purdum, Ben Rusholme, Jesper Sollerman, Mansi M. Kasliwal

CoRR, December, 2025

DataS^3: Dataset Subset Selection for Specialization.

Neha Hulkund, Alaa Maalouf, Levi Cai, Daniel Yang, Tsun-Hsuan Wang, Abigail O'Neil, Timm Haucke, Sandeep Mukherjee, Vikram Ramaswamy, Judy Hansen Shen, Gabriel Tseng, Mike Walmsley, Daniela Rus, Ken Goldberg, Hannah Kerner, Irene Chen, Yogesh A. Girdhar, Sara Beery

CoRR, April, 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, April, 2025

SIDDA: SInkhorn Dynamic Domain Adaptation for Image Classification with Equivariant Neural Networks.

Sneh Pandya, Purvik Patel, Brian Nord, Mike Walmsley, Aleksandra Ciprijanovic

CoRR, January, 2025

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

Scaling Laws for Galaxy Images.

Mike Walmsley, Micah Bowles, Anna M. M. Scaife, Jason Shingirai Makechemu, Alexander J. Gordon, Annette M. N. Ferguson, Robert G. Mann, James Pearson, Jürgen J. Popp, Jo Bovy, Joshua S. Speagle, Hugh Dickinson, Lucy Fortson, Tobias Géron, Sandor Kruk, Chris J. Lintott, Kameswara Bharadwaj Mantha, Devina Mohan, David O'Ryan, Inigo V. Slijepcevic

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 37: Annual Conference on Neural Information Processing Systems 2024, 2024

2023

Zoobot: Adaptable Deep Learning Models for Galaxy Morphology.

Mike Walmsley, Campbell Allen, Ben Aussel, Micah Bowles, Kasia Gregorowicz, Inigo Val Slijepcevic, Chris J. Lintott, Anna M. M. Scaife, Maja Jablonska, Kosio Karchev, Denise Lanzieri, Devina Mohan, David O'Ryan, Bharath Saiguhan, Crisel Suárez, Nicolás Guerra-Varas, Renuka Velu

J. Open Source Softw., July, 2023

Rare Galaxy Classes Identified In Foundation Model Representations.

Mike Walmsley, Anna M. M. Scaife

CoRR, 2023

Deep Learning Segmentation of Spiral Arms and Bars.

Mike Walmsley, Ashley Spindler

CoRR, 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, Tobias 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, Elad Zinger

CoRR, 2023

2022

A New Task: Deriving Semantic Class Targets for the Physical Sciences.

Micah Bowles, Hongming Tang, Eleni Vardoulaki, Emma L. Alexander, Yan Luo, Lawrence Rudnick, Mike Walmsley, Fiona Porter, Anna M. M. Scaife, Inigo Val Slijepcevic, Gary Segal

CoRR, 2022

Towards Galaxy Foundation Models with Hybrid Contrastive Learning.

Mike Walmsley, Inigo Val Slijepcevic, Micah Bowles, Anna M. M. Scaife

CoRR, 2022

Radio Galaxy Zoo: Using semi-supervised learning to leverage large unlabelled data-sets for radio galaxy classification under data-set shift.

Inigo V. Slijepcevic, Anna M. M. Scaife, Mike Walmsley, Micah Bowles, Ivy Wong, Stanislav S. Shabala, Hongming Tang

CoRR, 2022

Quantifying Uncertainty in Deep Learning Approaches to Radio Galaxy Classification.

Devina Mohan, Anna M. M. Scaife, Fiona Porter, Mike Walmsley, Micah Bowles

CoRR, 2022

A new Workflow for Human-AI Collaboration in Citizen Science.

Ya'akov (Kobi) Gal, Avi Segal, Ece Kamar, Eric Horvitz, Chris J. Lintott, Mike Walmsley

Proceedings of the GoodIT 2022: ACM International Conference on Information Technology for Social Good, Limassol, Cyprus, September 7, 2022

2021

Practical Galaxy Morphology Tools from Deep Supervised Representation Learning.

Mike Walmsley, Anna M. M. Scaife, Chris J. Lintott, Michelle Lochner, Verlon Etsebeth, Tobias Géron, Hugh Dickinson, Lucy Fortson, Sandor Kruk, Karen L. Masters, Kameswara Bharadwaj Mantha, Brooke D. Simmons

CoRR, 2021

Revisiting Citizen Science Through the Lens of Hybrid Intelligence.

Janet Rafner, Miroslav Gajdacz, Gitte Kragh, Arthur Hjorth, Anna Jia Gander, Blanka Palfi, Aleks Berditchevskaia, François Grey, Kobi Gal, Avi Segal, Mike Walmsley, Josh Aaron Miller, Dominik Dellerman, Muki Haklay, Pietro Michelucci, Jacob Friis Sherson

CoRR, 2021

Galaxy Zoo DECaLS: Detailed Visual Morphology Measurements from Volunteers and Deep Learning for 314, 000 Galaxies.

Mike Walmsley, Chris J. Lintott, Tobias Géron, Sandor Kruk, Coleman Krawczyk, Kyle W. Willett, Steven Bamford, William Keel, Lee S. Kelvin, Lucy Fortson, Karen L. Masters, Vihang Mehta, Brooke D. Simmons, Rebecca J. Smethurst, Elisabeth M. Baeten, Christine Macmillan

CoRR, 2021

2019

Help Me to Help You: Machine Augmented Citizen Science.

Darryl Wright, Lucy Fortson, Chris J. Lintott, Michael Laraia, Mike Walmsley

ACM Trans. Soc. Comput., 2019

Galaxy Zoo: Probabilistic Morphology through Bayesian CNNs and Active Learning.

Mike Walmsley, Lewis Smith, Chris J. Lintott, Yarin Gal, Steven Bamford, Hugh Dickinson, Lucy Fortson, Sandor Kruk, Karen Masters, Claudia Scarlata, Brooke Simmons, Rebecca J. Smethurst, Darryl Wright

CoRR, 2019