4 papers
Residual Reweighted Conformal Prediction for Graph Neural Networks
Zheng Zhang, Jie Bao, Zhixin Zhou +3
Graph Neural Networks (GNNs) excel at modeling relational data but face significant challenges in high-stakes domains due to unquantified uncertainty. Conformal prediction (CP) off…
Enhancing Adversarial Robustness with Conformal Prediction: A Framework for Guaranteed Model Reliability
Jie Bao, Chuangyin Dang, Rui Luo +2
As deep learning models are increasingly deployed in high-risk applications, robust defenses against adversarial attacks and reliable performance guarantees become paramount. Moreo…
Game-Theoretic Defenses for Robust Conformal Prediction Against Adversarial Attacks in Medical Imaging
Rui Luo, Jie Bao, Zhixin Zhou +1
Adversarial attacks pose significant threats to the reliability and safety of deep learning models, especially in critical domains such as medical imaging. This paper introduces a…
Structure-Aware Stylized Image Synthesis for Robust Medical Image Segmentation
Jie Bao, Zhixin Zhou, Wen Jung Li +1
Accurate medical image segmentation is essential for effective diagnosis and treatment planning but is often challenged by domain shifts caused by variations in imaging devices, ac…