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Objectives Matter: Understanding the Impact of Self-Supervised Objectives on Vision Transformer Representations.

, , , and . CoRR, (2023)

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Learning to Generate Samples from Noise through Infusion Training., , and . ICLR (Poster), OpenReview.net, (2017)Objectives Matter: Understanding the Impact of Self-Supervised Objectives on Vision Transformer Representations., , , and . CoRR, (2023)Predicting masked tokens in stochastic locations improves masked image modeling., , , , , , , , and . CoRR, (2023)PUG: Photorealistic and Semantically Controllable Synthetic Data for Representation Learning., , , , , and . CoRR, (2023)The hidden uniform cluster prior in self-supervised learning., , , , , , , , and . ICLR, OpenReview.net, (2023)Feedback-guided Data Synthesis for Imbalanced Classification., , , , and . CoRR, (2023)Do SSL Models Have Déjà Vu? A Case of Unintended Memorization in Self-supervised Learning., , , , and . CoRR, (2023)Guillotine Regularization: Improving Deep Networks Generalization by Removing their Head., , , , and . CoRR, (2022)A Cookbook of Self-Supervised Learning., , , , , , , , , and 9 other author(s). CoRR, (2023)Implementation Guidelines for Image Processing with Convolutional Neural Networks., and . MoMM, page 337-341. ACM, (2016)