3 citations · 6 across the 15 of their papers we have counts for
16 papers
CARE-VI: Conservative Adaptive Reliability Estimation for Value Improvement in Off-Policy Actor-Critic Learning
Xiang Zou, Shengzhu Shi, Junqi Gao +1
Reliable temporal-difference targets are central to off-policy actor-critic learning. Direct value improvement refines the next-state target with alternative actions, but the relia…
Latent Geometric Chords for Query-Efficient Decision-Based Adversarial Attacks
Ei Hmue Khine, Yao Li, Jiebao Sun +3
While decision-based black-box adversarial attacks present a severe security threat, current methodologies suffer from fundamental limitations. Pixel-wise attacks frequently introd…
Auto-FlexSwitch: Efficient Dynamic Model Merging via Learnable Task Vector Compression
Junqi Gao, Dazhi Zhang, Zhichang Guo +3
Model merging has attracted attention as an effective path toward multi-task adaptation by integrating knowledge from multiple task-specific models. Among existing approaches, dyna…
PDAC: Efficient Coreset Selection for Continual Learning via Probability Density Awareness
Junqi Gao, Zhichang Guo, Dazhi Zhang +3
Rehearsal-based Continual Learning (CL) maintains a limited memory buffer to store replay samples for knowledge retention, making these approaches heavily reliant on the quality of…
SAR-FAH: A Frequency-Adaptive Hybrid Network based on Neural ODEs for Structural-Preserving SAR Despeckling
Ziqing Ma, Chang Yang, Zhichang Guo +1
Synthetic Aperture Radar (SAR) images are inherently degraded by speckle noise that severely limits their reliability in high-precision applications. As a signal-dependent multipli…
TA-LSDiff:Topology-Aware Diffusion Guided by a Level Set Energy for Pancreas Segmentation
Yue Gou, Fanghui Song, Yuming Xing +3
Pancreas segmentation in medical image processing is a persistent challenge due to its small size, low contrast against adjacent tissues, and significant topological variations. Tr…
Progressive Alignment Degradation Learning for Pansharpening
Enzhe Zhao, Zhichang Guo, Yao Li +2
Deep learning-based pansharpening has been shown to effectively generate high-resolution multispectral (HRMS) images. To create supervised ground-truth HRMS images, synthetic data…
Bohdi: Heterogeneous LLM Fusion with Automatic Data Exploration
Junqi Gao, Zhichang Guo, Dazhi Zhang +5
Heterogeneous Large Language Model (LLM) fusion integrates the strengths of multiple source LLMs with different architectures into a target LLM with low computational overhead. Whi…
A class of thin-film equations with space-time dependent gradient nonlinearity and its application to image sharpening
Yuhang Li, Zhichang Guo, Fanghui Song +2
We introduce a class of thin-film equations with space-time dependent gradient nonlinearity and apply them to image sharpening. By modifying the potential well method, we overcome…
A Tunable Despeckling Neural Network Stabilized via Diffusion Equation
Yi Ran, Zhichang Guo, Jia Li +3
The removal of multiplicative Gamma noise is a critical research area in the application of synthetic aperture radar (SAR) imaging, where neural networks serve as a potent tool. Ho…
Adversarial Transferability in Deep Denoising Models: Theoretical Insights and Robustness Enhancement via Out-of-Distribution Typical Set Sampling
Jie Ning, Jiebao Sun, Shengzhu Shi +4
Deep learning-based image denoising models demonstrate remarkable performance, but their lack of robustness analysis remains a significant concern. A major issue is that these mode…
Perturbation Towards Easy Samples Improves Targeted Adversarial Transferability
Junqi Gao, Biqing Qi, Yao Li +4
The transferability of adversarial perturbations provides an effective shortcut for black-box attacks. Targeted perturbations have greater practicality but are more difficult to tr…
Diffusion Probabilistic Multi-cue Level Set for Reducing Edge Uncertainty in Pancreas Segmentation
Yue Gou, Yuming Xing, Shengzhu Shi +1
Accurately segmenting the pancreas remains a huge challenge. Traditional methods encounter difficulties in semantic localization due to the small volume and distorted structure of…
Variable-order fractional 1-Laplacian diffusion equations for multiplicative noise removal
Yuhang Li, Zhichang Guo, Jingfeng Shao +2
In this paper, we study a class of fractional -Laplacian diffusion equations with variable orders, proposed as a model for multiplicative noise removal. The existence and unique…
PINNsFailureRegion Localization and Refinement through White-box AdversarialAttack
Shengzhu Shi, Yao Li, Zhichang Guo +2
Physics-informed neural networks (PINNs) have shown great promise in solving partial differential equations (PDEs). However, vanilla PINNs often face challenges when solving comple…
Re-initialization-free Level Set Method via Molecular Beam Epitaxy Equation Regularization for Image Segmentation
Fanghui Song, Jiebao Sun, Shengzhu Shi +2
Variational level set method has become a powerful tool in image segmentation due to its ability to handle complex topological changes and maintain continuity and smoothness in the…