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 ...
Abstract: Next Point-of-interest recommendation involves modeling user interactions with Point-of-interests (PoIs) to analyze user behavior patterns and suggest future scenarios. Data sparsity ...
Abstract: High-efficiency compression of the ECG signal is crucial for minimizing transmission bandwidth and power consumption in healthcare and Internet of Things (IoT) systems. In this work, the ...