Michelle Lochner

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 9

Top Topics

Multivariate Time Series

Anomaly Detection

Anomalous Behavior

One Class Support Vector Machines

Top Venues

Astron. Comput.

Int. J. Hybrid Intell. Syst.

Publications

Rithwik Gupta, Daniel Muthukrishna, Michelle Lochner
A Classifier-Based Approach to Multi-Class Anomaly Detection for Astronomical Transients. CoRR (2024)
Michelle Lochner, Bruce A. Bassett
Astronomaly: Personalised active anomaly detection in astronomical data. Astron. Comput. 36 (2021)
Daniel Muthukrishna, Kaisey S. Mandel, Michelle Lochner, Sara Webb, Gautham Narayan
Real-time Detection of Anomalies in Multivariate Time Series of Astronomical Data. CoRR (2021)
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
Practical Galaxy Morphology Tools from Deep Supervised Representation Learning. CoRR (2021)
Daniel Muthukrishna, Kaisey S. Mandel, Michelle Lochner, Sara Webb, Gautham Narayan
Real-time detection of anomalies in large-scale transient surveys. CoRR (2021)
Ethan Roberts, Bruce A. Bassett, Michelle Lochner
Bayesian anomaly detection and classification for noisy data. Int. J. Hybrid Intell. Syst. 16 (4) (2020)
Ethan Roberts, Bruce A. Bassett, Michelle Lochner
Bayesian Anomaly Detection and Classification for Noisy Data. ISDA (2019)
Ethan Roberts, Bruce A. Bassett, Michelle Lochner
Bayesian Anomaly Detection and Classification. CoRR (2019)
Alireza Vafaei Sadr, Etienne E. Vos, Bruce A. Bassett, Zafiirah Hosenie, N. Oozeer, Michelle Lochner
DeepSource: Point Source Detection using Deep Learning. CoRR (2018)