44 citations · 186 across the 25 of their papers we have counts for
25 papers
A Ferroelectric Compute-in-Memory Annealer for Combinatorial Optimization Problems
Xunzhao Yin, Yu Qian, Alptekin Vardar +11
Computationally hard combinatorial optimization problems (COPs) are ubiquitous in many applications, including logistical planning, resource allocation, chip design, drug explorati…
Masked Diffusion as Self-supervised Representation Learner
Zixuan Pan, Jianxu Chen, Yiyu Shi
Denoising diffusion probabilistic models have recently demonstrated state-of-the-art generative performance and have been used as strong pixel-level representation learners. This p…
Improving Realistic Worst-Case Performance of NVCiM DNN Accelerators through Training with Right-Censored Gaussian Noise
Zheyu Yan, Yifan Qin, Wujie Wen +2
Compute-in-Memory (CiM), built upon non-volatile memory (NVM) devices, is promising for accelerating deep neural networks (DNNs) owing to its in-situ data processing capability and…
Toward Fairness Through Fair Multi-Exit Framework for Dermatological Disease Diagnosis
Ching-Hao Chiu, Hao-Wei Chung, Yu-Jen Chen +2
Fairness has become increasingly pivotal in medical image recognition. However, without mitigating bias, deploying unfair medical AI systems could harm the interests of underprivil…
How to Efficiently Adapt Large Segmentation Model(SAM) to Medical Images
Xinrong Hu, Xiaowei Xu, Yiyu Shi
The emerging scale segmentation model, Segment Anything (SAM), exhibits impressive capabilities in zero-shot segmentation for natural images. However, when applied to medical image…
AME-CAM: Attentive Multiple-Exit CAM for Weakly Supervised Segmentation on MRI Brain Tumor
Yu-Jen Chen, Xinrong Hu, Yiyu Shi +1
Magnetic resonance imaging (MRI) is commonly used for brain tumor segmentation, which is critical for patient evaluation and treatment planning. To reduce the labor and expertise r…