Abstract: Variational Graph Autoencoders (VAGE) emerged as powerful graph representation learning methods with promising performance on graph analysis tasks. However, existing methods typically rely ...

We present Representation Autoencoders (RAE), a class of autoencoders that utilize pretrained, frozen representation encoders such as DINOv2 and SigLIP2 as encoders with trained ViT decoders. RAE can ...

MAESTRO_FLAIR-HUB_base — pre-trained on FLAIR-HUB MAESTRO_S2-NAIP-urban_base — pre-trained on S2-NAIP-urban Land cover segmentation in France, with 12 semantic classes. Note that the FLAIR#2 version ...

Abstract: Nowadays, face recognition technology has been dramatically boosted by the advances in deep learning and big data fields. However, this also poses grand ...