
Curriculum learning enhances masked autoencoders for robust representation learning.


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cl-mae-curriculum-learned-masked-autoencoders-unveiled


CL-MAE: Curriculum-Learned Masked Autoencoders Unveiled


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MLVICXは胸部X線画像の自己教師付き表現学習のための多レベル分散共分散探索を紹介します。


mlvicx-multi-level-variance-covariance-exploration-for-chest-x-ray-self-supervised-representation-learning


MLVICX: Multi-Level Variance-Covariance Exploration for Chest X-ray Self-Supervised Representation Learning



The core message of this work is to propose the Multi-View Entropy Bottleneck (MVEB) objective to effectively learn the minimal sufficient representation in the unsupervised multi-view setting. MVEB simplifies the learning of the minimal sufficient representation to maximizing both the agreement between the embeddings of two views and the differential entropy of the embedding distribution.


mveb-self-supervised-learning-with-multi-view-entropy-bottleneck-for-minimal-sufficient-representation


MVEB: Self-Supervised Learning with Multi-View Entropy Bottleneck for Minimal Sufficient Representation
