Michelle Lochner

According to our database, Michelle Lochner authored at least 9 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2024

A Classifier-Based Approach to Multi-Class Anomaly Detection Applied to Astronomical Time-Series.

Rithwik Gupta, Daniel Muthukrishna, Michelle Lochner

CoRR, 2024

A Classifier-Based Approach to Multi-Class Anomaly Detection for Astronomical Transients.

Rithwik Gupta, Daniel Muthukrishna, Michelle Lochner

CoRR, 2024

2021

Real-time Detection of Anomalies in Multivariate Time Series of Astronomical Data.

Daniel Muthukrishna, Kaisey S. Mandel, Michelle Lochner, Sara Webb, Gautham Narayan

CoRR, 2021

Real-time detection of anomalies in large-scale transient surveys.

Daniel Muthukrishna, Kaisey S. Mandel, Michelle Lochner, Sara Webb, Gautham Narayan

CoRR, 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

Astronomaly: Personalised active anomaly detection in astronomical data.

Michelle Lochner, Bruce A. Bassett

Astron. Comput., 2021

2020

Bayesian anomaly detection and classification for noisy data.

Ethan Roberts, Bruce A. Bassett, Michelle Lochner

Int. J. Hybrid Intell. Syst., 2020

2019

Bayesian Anomaly Detection and Classification.

Ethan Roberts, Bruce A. Bassett, Michelle Lochner

CoRR, 2019

2018

DeepSource: Point Source Detection using Deep Learning.

Alireza Vafaei Sadr, Etienne E. Vos, Bruce A. Bassett, Zafiirah Hosenie, N. Oozeer, Michelle Lochner

CoRR, 2018