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[논문 리뷰] Representation Learning via Invariant Causal Mechanisms

논문 링크: Representation Learning via Invariant Causal MechanismsSelf-supervised learning has emerged as a strategy to reduce the reliance on costly supervised signal by pretraining representations only using unlabeled data. These methods combine heuristic proxy classification tasks with data augmentations and have achiarxiv.org 출처: J. Mitrovic, B. McWilliams, J. Walker, L. Buesing, and C. Blundel..

Artificial Intelligence 2026.02.10
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beyond 6G, semantic learning, energy efficiency, Semantic communications, Federated Learning, 6g, ML, orthogonal frequency division multiplexing (OFDM), AI-native, Intelligent wireless networks, massive MIMO systems, Joint source-channel coding, time-division duplexing (TDD), Large Language Model, Ai, spectral efficiency, contextual reasoning, Channel estimation, pilotcontamination, semantic communication,

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