This article describes a new method for generating music symbolically, using a graph that represents the structure of a song and a Graph Neural Network. The graph uses information such…
Continue readingThe study focuses on the challenge of structural divergence in pre-training and fine-tuning Graph Neural Networks (GNNs). It identifies the root cause as the discrepancy of generative patterns between pre-training…
Continue readingThis research proposes a novel solution for medical image classification using Graph Neural Networks (GNNs). The approach uses Image Foresting Transform to segment images, which are then transformed into graph-structured…
Continue readingThe article introduces ATGNN (Audio Tagging Graph Neural Network), a deep learning model for audio tagging. It addresses the limitations of CNNs and Transformers by treating the spectrogram as a…
Continue readingThis research paper presents a new method, named SAP, to improve Graph Neural Networks (GNNs). GNNs are effective at learning semantics of graph data. However, the structure information of a…
Continue readingThe article introduces BLIS-Net, a novel Graph Neural Network (GNN) designed for signal classification. Unlike traditional GNNs, BLIS-Net can capture both local and global signal structures, as well as low…
Continue readingThe research introduces a novel approach in circuit design by using artificial intelligence technologies. The most time-consuming parts of the physical design process are placement and routing. This research proposes…
Continue readingThe paper explores the application of Knowledge Graph Embeddings (KGE) and Graph Neural Networks (GNN) in the context of the Web of Things (WoT). The focus is on how these…
Continue readingThe article presents MolCA, a molecular graph-language modeling method which enhances Language Models’ (LMs) understanding of molecules. Traditional LMs lack a comprehension of 2D graph perception, which is essential for…
Continue readingThe paper proposes a federated heterogeneous graph neural network (FedHGNN) for privacy-preserving recommendations. The authors suggest that the Heterogeneous Information Network (HIN) is partitioned into private HINs stored on the…
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