5 citations · 5 across the 27 of their papers we have counts for
9 papers · 1 filter
AnyAD: Unified Any-Modality Anomaly Detection in Incomplete Multi-Sequence MRI
Changwei Wu, Yifei Chen, Yuxin Du +7
Reliable anomaly detection in brain MRI remains challenging due to the scarcity of annotated abnormal cases and the frequent absence of key imaging modalities in real clinical work…
Constructive Approximation under Carleman's Condition, with Applications to Smoothed Analysis
Frederic Koehler, Beining Wu
A classical result of Carleman, based on the theory of quasianalytic functions, shows that polynomials are dense in for any such that the moments do not…
A Large Scale Benchmark for Test Time Adaptation Methods in Medical Image Segmentation
Wenjing Yu, Shuo Jiang, Yifei Chen +9
Test time Adaptation is a promising approach for mitigating domain shift in medical image segmentation; however, current evaluations remain limited in terms of modality coverage, t…
A Tale of Two Geometries: Adaptive Optimizers and Non-Euclidean Descent
Shuo Xie, Tianhao Wang, Beining Wu +1
Adaptive optimizers can reduce to normalized steepest descent (NSD) when only adapting to the current gradient, suggesting a close connection between the two algorithmic families.…
SmaRT: Style-Modulated Robust Test-Time Adaptation for Cross-Domain Brain Tumor Segmentation in MRI
Yuanhan Wang, Yifei Chen, Shuo Jiang +7
Reliable brain tumor segmentation in MRI is indispensable for treatment planning and outcome monitoring, yet models trained on curated benchmarks often fail under domain shifts ari…
Prior-Guided Residual Diffusion: Calibrated and Efficient Medical Image Segmentation
Fuyou Mao, Beining Wu, Yanfeng Jiang +3
Ambiguity in medical image segmentation calls for models that capture full conditional distributions rather than a single point estimate. We present Prior-Guided Residual Diffusion…
Towards Theoretical Understanding of Transformer Test-Time Computing: Investigation on In-Context Linear Regression
Xingwu Chen, Miao Lu, Beining Wu +1
Using more test-time computation during language model inference, such as generating more intermediate thoughts or sampling multiple candidate answers, has proven effective in sign…
"X of Information'' Continuum: A Survey on AI-Driven Multi-dimensional Metrics for Next-Generation Networked Systems
Beining Wu, Jun Huang, Shui Yu
The development of next-generation networking systems has inherently shifted from throughput-based paradigms towards intelligent, information-aware designs that emphasize the quali…
Enhancing Vehicular Platooning with Wireless Federated Learning: A Resource-Aware Control Framework
Beining Wu, Jun Huang, Qiang Duan +2
This paper aims to enhance the performance of Vehicular Platooning (VP) systems integrated with Wireless Federated Learning (WFL). In highly dynamic environments, vehicular platoon…