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Zepeng Zhang

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Publications associées (4)

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Graph Neural Networks With Adaptive Structures

Zepeng Zhang

Graph neural networks (GNNs) have made significant progress in various machine learning tasks. Despite their success, many existing GNN models are shown to be vulnerable to adversarial attacks, creating a stringent need to build robust GNN architectures. I ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2025

Accelerating Quadratic Transform and WMMSE

Zepeng Zhang

Fractional programming (FP) arises in various communications and signal processing problems because several key quantities in these fields are fractionally structured, e.g., the Cram & eacute;r-Rao bound, the Fisher information, and the signal-to-interfere ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2024

A Joint Graph Signal and Laplacian Denoising Network

Zepeng Zhang

Graph neural network (GNN) models have presented astonishing achievements in various application fields. However, they are shown to be vulnerable to adversarial attacks on graph structure and unnoticeable perturbations on the graph structure can cause sign ...

Institute of Electrical and Electronics Engineers Inc.2024

Domain Adaptive Unfolded Graph Neural Networks

Olga Fink, Zepeng Zhang

Over the last decade, graph neural networks (GNNs) have made significant progress in numerous graph machine learning tasks. In real-world applications, where domain shifts occur and labels are often unavailable for a new target domain, graph domain adaptat ...

Association for the Advancement of Artificial Intelligence2025