Dickinson, Hugh

Galaxy Zoo: probabilistic morphology through Bayesian CNNs and active learning

Walmsley, M., Smith, L., Lintott, C., Gal, Y., Bamford, S., Dickinson, H., Fortson, L., Kruk, S., Masters, K., Scarlata, C., et al. (2020) · Monthly Notices of the Royal Astronomical Society

Galaxies: Formation, Evolution, PhenomenaAdvanced Neural Network Applications

Cited by 160

Practical Galaxy Morphology Tools from Deep Supervised Representation Learning

Walmsley, M., Scaife, A. M. M., Lintott, C., Lochner, M., Etsebeth, V., Géron, T., Dickinson, H., Fortson, L., Kruk, S., Masters, K. L., et al. (2021) · arXiv

Galaxies: Formation, Evolution, PhenomenaAdvanced Neural Network Applications

Cited by 64

Detecting gravitational lenses using machine learning: exploring interpretability and sensitivity to rare lensing configurations

Wilde, J., Serjeant, S., Bromley, J. M., Dickinson, H., Koopmans, L. V. E., & Metcalf, R. B. (2022) · Monthly Notices of the Royal Astronomical Society

Galaxies: Formation, Evolution, PhenomenaAstrophysical Phenomena and Observations

Cited by 31

Euclid : Searches for strong gravitational lenses using convolutional neural nets in Early Release Observations of the Perseus field

Pearce-Casey, R., Nagam, B. C., Wilde, J., Busillo, V., Ulivi, L., Andika, I. T., Manjón-García, A., Leuzzi, L., Matavulj, P., Serjeant, S., et al. (2025) · Astronomy & Astrophysics

Galaxies: Formation, Evolution, PhenomenaAstrophysical Phenomena and Observations

Cited by 18

Scaling Laws for Galaxy Images

Walmsley, M., Bowles, M., Scaife, A. M. M., Makechemu, J. S., Gordon, A. J., Ferguson, A. M. N., Mann, R. G., Pearson, J., Popp, J. J., Bovy, J., et al. (2024) · arXiv

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 2