Unifying Graph Convolution and Contrastive Learning in Collaborative Filtering The paper was accepted by SIGKDD 2024. In this paper, we show the equivalence of graph convolutions and contrastive ...

Previous methods for multigraph rather lacks cross-view interaction or are too inefficient to be used in practice. We propose a simple and efficient multigraph convolutional networks based on both ...

HRS-Net: A Hybrid Multi-Scale Network Model Based on Convolution and Transformers for Multi-Class Retinal Disease Classification ...

To determine how listeners learn the statistical properties of acoustic spaces, we assessed their ability to perceive speech in a range of noisy and reverberant rooms. Listeners were also exposed to ...