4 papers
Incremental Learning with Repetition via Pseudo-Feature Projection
Benedikt Tscheschner, Eduardo Veas, Marc Masana
Incremental Learning scenarios do not always represent real-world inference use-cases, which tend to have less strict task boundaries, and exhibit repetition of common classes and…
Leveraging Intermediate Representations for Better Out-of-Distribution Detection
Gianluca Guglielmo, Marc Masana
In real-world applications, machine learning models must reliably detect Out-of-Distribution (OoD) samples to prevent unsafe decisions. Current OoD detection methods often rely on…
Continual Learning in the Presence of Repetition
Hamed Hemati, Lorenzo Pellegrini, Xiaotian Duan +11
Continual learning (CL) provides a framework for training models in ever-evolving environments. Although re-occurrence of previously seen objects or tasks is common in real-world p…
On the importance of cross-task features for class-incremental learning
Albin Soutif--Cormerais, Marc Masana, Joost van de Weijer +1
In class-incremental learning, an agent with limited resources needs to learn a sequence of classification tasks, forming an ever growing classification problem, with the constrain…