Mike Walmsley

Orcid: 0000-0002-6408-4181

According to our database1, Mike Walmsley authored at least 16 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
pathfinder: A Semantic Framework for Literature Review and Knowledge Discovery in Astronomy.
CoRR, 2024

Scaling Laws for Galaxy Images.
CoRR, 2024

2023
Zoobot: Adaptable Deep Learning Models for Galaxy Morphology.
J. Open Source Softw., July, 2023

Rare Galaxy Classes Identified In Foundation Model Representations.
CoRR, 2023

Deep Learning Segmentation of Spiral Arms and Bars.
CoRR, 2023

Constructing Impactful Machine Learning Research for Astronomy: Best Practices for Researchers and Reviewers.
CoRR, 2023

2022
A New Task: Deriving Semantic Class Targets for the Physical Sciences.
CoRR, 2022

Towards Galaxy Foundation Models with Hybrid Contrastive Learning.
CoRR, 2022

Radio Galaxy Zoo: Using semi-supervised learning to leverage large unlabelled data-sets for radio galaxy classification under data-set shift.
CoRR, 2022

Quantifying Uncertainty in Deep Learning Approaches to Radio Galaxy Classification.
CoRR, 2022

A new Workflow for Human-AI Collaboration in Citizen Science.
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.
CoRR, 2021

Revisiting Citizen Science Through the Lens of Hybrid Intelligence.
CoRR, 2021

Galaxy Zoo DECaLS: Detailed Visual Morphology Measurements from Volunteers and Deep Learning for 314, 000 Galaxies.
CoRR, 2021

2019
Help Me to Help You: Machine Augmented Citizen Science.
ACM Trans. Soc. Comput., 2019

Galaxy Zoo: Probabilistic Morphology through Bayesian CNNs and Active Learning.
CoRR, 2019


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