we propose a novel perspective of augmentation to regularize the training process. Inspired by the recent success of applying masked image modeling to self-supervised learning, we adopt the self-supervised masked autoencoder to generate the distorted view of the input images. We show that utilizing...
This repository is the official implementation of“Denoising Masked Autoencoders Help Robust Classification”, based on the official implementation ofMAEinPyTorch. @inproceedings{wu2023dmae, title={Denoising Masked Autoencoders Help Robust Classification}, author={Wu, QuanLin and Ye, Hang and Gu, Yun...
* 题目: Surface Masked AutoEncoder: Self-Supervision for Cortical Imaging Data* PDF: arxiv.org/abs/2308.0547* 作者: Simon Dahan,Mariana da Silva,Daniel Rueckert,Emma C Robinson* 相关: github.com/metrics-lab/ 其他任务中的小样本学习 1篇 * 题目: Exploring Linguistic Similarity and Zero-Shot ...
* Multi-Modal Masked Autoencoders for Medical Vision-and-Language Pre-Training * 链接:https://arxiv.org/abs/2209.07098 * 作者: Zhihong Chen,Yuhao Du,Jinpeng Hu,Yang Liu,Guanbin Li,Xiang Wan,Tsung-Hui Chang * 其他: Natural Language Processing. 11 pages, 3 figures * 摘要: 医学视觉和语言...
In the class-conditional reconstruction process, a masking mechanism is applied to output capsules, where the capsules, corresponding to non-ground-truth classes, are masked with zeros. The input image is reconstructed from the masked output capsules. The reconstruction loss ...
The XLM-RoBERTa model is a Transformer-based large language model that was pre-trained with the masked language modeling objective, where some of the words in the text are masked and the model is trained to predict the correct word. A Transformer is a neural network architecture, which ...
This repository is the official implementation of “Denoising Masked Autoencoders Help Robust Classification”, based on the official implementation of MAE in PyTorch. @inproceedings{wu2023dmae, title={Denoising Masked Autoencoders Help Robust Classification}, author={Wu, QuanLin and Ye, Hang and Gu...