… This does not guarantee that the encoder we learn will be strictly equivariant to the group. In
… exists an encoder that is non-trivially equivariant, under a reasonable assumption which is …

… learning models to learn rotation-equivariant representation and SIR. Through learning
rotation … our method and other contrastive representation learning methods, such as CPC [22…

… Care, an equivariant contrastive learning framework that … (the standard space for contrastive
learning), so we specifically … prior non-linear formulations, our learning problem is more …

… introduce a novel contrastive learning approach to learn representations equivariant to a set
… learning; 4) We show that time-equivariant representations achieve state-of-the-art transfer …

… To achieve this, we generalize invariant contrastive learning to equivariant contrastive
learning (ECL) for SR. We show the high-level structure of the framework in Fig. 2. …

… VMamba-based contrastive learning has outstanding … equivariant representations into
DINO through our stabilized DDCL, we propose a novel equivariant-based contrastive learning …

… presenting a unified view of the equivariant and invariant learning approaches. We show that
… We also observe that objectives used in equivariant learning can be seen as a contrastive …

… using self-supervised learning (SSL) approaches for learning feature representations with
unlabeled data. Such SSL approaches include contrastive learning methods such as SimCLR …

… Critically, we can easily integrate CARE into contrastive learning workflows since both …
used in self supervised learning This work introduces CARE, an equivariant contrastive learning …

… Contrastive learning is a simple and effective method to … Our method extends the conventional
contrastive learning by … To allow the combination of invariant and equivariant learning, we …