Second, it extracts the encoder and feature learning module from the masked autoencoder, utilizing them as the teacher model. In MACD, the knowledge distillation step involves training the model with ...

ABSTRACT: Deep learning (DL) techniques, more specifically Convolutional Neural Networks (CNNs), have become increasingly popular in advancing the field of data science and have had great successes in ...

Remarkably, our method takes a careful consideration of positive pairs for contrastive learning with negligible extra training overhead. As a plug-and-play and framework-agnostic module, ...

Official PyTorch implementation of the AAAI 2022 paper Ranking Info Noise Contrastive Estimation: Boosting Contrastive Learning via Ranked Positives. The code allows the users to reproduce and extend ...