A comprehensive survey on contrastive learning

Published: 01 Jan 2024, Last Modified: 13 Nov 2024Neurocomputing 2024EveryoneRevisionsBibTeXCC BY-SA 4.0
Abstract: Highlights•Main ideas, recent developments and applications are systematically sorted out.•Some significant progresses are introduced from different perspectives.•Challenges, directions and future trends of contrastive learning are discussed.
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