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May, 2024
PhiNets:基于时间预测假设的脑启发非对比学习
PhiNets: Brain-inspired Non-contrastive Learning Based on Temporal Prediction Hypothesis
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Satoki Ishikawa, Makoto Yamada, Han Bao, Yuki Takezawa
TL;DR
PhiNet是一种受海马模型启发的方法,通过整合额外的预测模块和动量编码器模块,解决了SimSiam在权重衰减敏感性和在线连续学习性能方面存在的问题,并在内存密集型任务中表现更稳健、更好。
Abstract
simsiam
is a prominent
self-supervised learning
method that achieves impressive results in various vision tasks under static environments. However, it has two critical issues: high sensitivity to hyperparameters,
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