Meet the authors: Georgios Rizos, Jenna L. Lawson, and Björn W. Schuller

Georgios Rizos, Jenna L. Lawson, Björn W. Schuller

Research output: Contribution to journalComment/debate

Abstract

In their recent publication in Patterns, the authors proposed a methodology based on sample-free Bayesian neural networks and label smoothing to improve both predictive and calibration performance on animal call detection. Such approaches have the potential to foster trust in algorithmic decision making and enhance policy making in applications about conservation using recordings made by on-site passive acoustic monitoring equipment. This interview is a companion to these authors’ recent paper, “Propagating Variational Model Uncertainty for Bioacoustic Call Label Smoothing”.

Original languageEnglish
Article number100952
JournalPatterns
Volume5
Issue number3
DOIs
StatePublished - 8 Mar 2024

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