108 citations · 222 across the 9 of their papers we have counts for
9 papers
Self-Supervised Clustering on Image-Subtracted Data with Deep-Embedded Self-Organizing Map
Y. -L. Mong, K. Ackley, T. L. Killestein +45
Developing an effective automatic classifier to separate genuine sources from artifacts is essential for transient follow-ups in wide-field optical surveys. The identification of t…
The Gravitational-wave Optical Transient Observer (GOTO): prototype performance and prospects for transient science
D. Steeghs, D. K. Galloway, K. Ackley +50
The Gravitational-wave Optical Transient Observer (GOTO) is an array of wide-field optical telescopes, designed to exploit new discoveries from the next generation of gravitational…
Searching For Fermi GRB Optical Counterparts With The Prototype Gravitational-Wave Optical Transient Observer (GOTO)
Y. -L. Mong, K. Ackley, D. K. Galloway +45
The typical detection rate of gamma-ray burst (GRB) per day by the \emph{Fermi} Gamma-ray Burst Monitor (GBM) provides a valuable opportunity to further our understanding o…
Light curve classification with recurrent neural networks for GOTO: dealing with imbalanced data
U. F. Burhanudin, J. R. Maund, T. Killestein +42
The advent of wide-field sky surveys has led to the growth of transient and variable source discoveries. The data deluge produced by these surveys has necessitated the use of machi…
Processing GOTO data with the Rubin Observatory LSST Science Pipelines II: Forced Photometry and light curves
L. Makrygianni, J. Mullaney, V. Dhillon +45
We have adapted the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) Science Pipelines to process data from the Gravitational-Wave Optical Transient Observer (GOTO)…
Transient-optimised real-bogus classification with Bayesian Convolutional Neural Networks -- sifting the GOTO candidate stream
T. L. Killestein, J. Lyman, D. Steeghs +45
Large-scale sky surveys have played a transformative role in our understanding of astrophysical transients, only made possible by increasingly powerful machine learning-based filte…
Processing GOTO data with the Rubin Observatory LSST Science Pipelines I : Production of coadded frames
J. R. Mullaney, L. Makrygianni, V. Dhillon +44
The past few decades have seen the burgeoning of wide field, high cadence surveys, the most formidable of which will be the Legacy Survey of Space and Time (LSST) to be conducted b…
Machine Learning for Transient Recognition in Difference Imaging With Minimum Sampling Effort
Yik-Lun Mong, Kendall Ackley, Duncan Galloway +45
The amount of observational data produced by time-domain astronomy is exponentially in-creasing. Human inspection alone is not an effective way to identify genuine transients fromt…
Searching for Electromagnetic Counterparts to Gravitational-wave Merger Events with the Prototype Gravitational-wave Optical Transient Observer (GOTO-4)
B. P. Gompertz, R. Cutter, D. Steeghs +49
We report the results of optical follow-up observations of 29 gravitational-wave triggers during the first half of the LIGO-Virgo Collaboration (LVC) O3 run with the Gravitational-…