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cs.LG2024
ScaleNet: Scale Invariance Learning in Directed Graphs
Qin Jiang, Chengjia Wang, Michael Lones +2
Graph Neural Networks (GNNs) have advanced relational data analysis but lack invariance learning techniques common in image classification. In node classification with GNNs, it is…
cs.LG2024
Scale-aware Message Passing For Graph Node Classification
Qin Jiang, Chengjia Wang, Michael Lones +2
Most Graph Neural Networks (GNNs) operate at the first-order scale, even though multi-scale representations are known to be crucial in domains such as image classification. In this…
cs.CV2024★ 1 cited
SeLoRA: Self-Expanding Low-Rank Adaptation of Latent Diffusion Model for Medical Image Synthesis
Yuchen Mao, Hongwei Li, Wei Pang +3
The persistent challenge of medical image synthesis posed by the scarcity of annotated data and the need to synthesize `missing modalities' for multi-modal analysis, underscored th…