14 citations · 17 across the 5 of their papers we have counts for
5 papers
MALPOLON: A Framework for Deep Species Distribution Modeling
Theo Larcher, Lukas Picek, Benjamin Deneu +3
This paper describes a deep-SDM framework, MALPOLON. Written in Python and built upon the PyTorch library, this framework aims to facilitate training and inferences of deep species…
Classification Under Ambiguity: When Is Average-K Better Than Top-K?
Titouan Lorieul, Alexis Joly, Dennis Shasha
When many labels are possible, choosing a single one can lead to low precision. A common alternative, referred to as top- classification, is to choose some number (commonly…
Multi-Label Learning from Single Positive Labels
Elijah Cole, Oisin Mac Aodha, Titouan Lorieul +3
Predicting all applicable labels for a given image is known as multi-label classification. Compared to the standard multi-class case (where each image has only one label), it is co…
Set-valued classification -- overview via a unified framework
Evgenii Chzhen, Christophe Denis, Mohamed Hebiri +1
Multi-class classification problem is among the most popular and well-studied statistical frameworks. Modern multi-class datasets can be extremely ambiguous and single-output predi…
The GeoLifeCLEF 2020 Dataset
Elijah Cole, Benjamin Deneu, Titouan Lorieul +6
Understanding the geographic distribution of species is a key concern in conservation. By pairing species occurrences with environmental features, researchers can model the relatio…