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cs.LG2025
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…
cs.LG2025
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…