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Daniel Marczak*

2 accepted papers

2024

MagMax: Leveraging Model Merging for Seamless Continual Learning

ECCV 2024poster

"This paper introduces a continual learning approach named , which utilizes model merging to enable large pre-trained models to continuously learn from new data without forgetting previously acquired knowledge. Distinct from traditional continual learning methods that aim to reduce forgetting during…

2024

Revisiting Supervision for Continual Representation Learning

ECCV 2024poster

"In the field of continual learning, models are designed to learn tasks one after the other. While most research has centered on supervised continual learning, there is a growing interest in unsupervised continual learning, which makes use of the vast amounts of unlabeled data. Recent studies have h…