PEIRA: Learning Predictive Encoders through Inter-View Regressor Alignment

ArXi:2605.17671v1 Announce Type: new Non-contrastive self-supervised learning (SSL) is an effective framework for predictive representation learning, but popular (and in practice effective) methods such as SimSiam, BYOL, I-JEPA or DINO, which rely on a form of self-distillation to train a teacher-student network, remain poorly understood as they typically do not minimize a well-defined objective.