… 39], our results indicate that contrastive self-supervised methods do not suffer from pretraining
… and improve contrastive self-supervised methods for learning visual representations. Self-…

… contrastive learning method SimCLR [7] and in section 4.2 we introduce attempts to improve
contrastive methods … Section 5.1 presents the model bias [44] in contrastive learning, and is …

… Our method shares the same spirit with these methods, in that we both use contrastive visual
representation … paths to better align the visual features with additional semantic information. …

… methods. We are able to use standard networks to obtain substantially better results compared
to previous methods … the comparisons of our results against recent methods (Zhai et al., …

… However, as we will show, applying these image view–based contrastive methods to medical
… In this work, we introduce a new method to improve visual representation learning on …

… method. We make the following contributions: (i) We introduce NNCLR to learn self-supervised
representations … increases the performance of contrastive learning methods (eg SimCLR […

… can degrade a self-supervised representation to the point of unusability … method. We focus
on SimCLR because it reflects the essence of state-of-the-art contrastive learning methods …

… We examine five different methods to analyze the effectiveness of contrastive learning in
tranferability, namely, CE, SelfSupCon, SupCon, CE+SelfSupCon, and SupCon+SelfSupCon. …

… Current self-supervised contrastive learning methods assume implicit knowledge of … to
learn visual representations which capture individual factors of variation in a contrastive learning …

… In this paper, we introduce a novel self-supervised visual representation learning method
which understands both images and videos in a joint learning fashion. The proposed neural …