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Rethinking Medical Anomaly Detection in Brain MRI: An Image Quality Assessment Perspective

Autor: Pan, Zixuan, Xia, Jun, Yan, Zheyu, Xu, Guoyue, Wu, Yawen, Jia, Zhenge, Chen, Jianxu, Shi, Yiyu

Reconstruction-based methods, particularly those leveraging autoencoders, have been widely adopted to perform anomaly detection in brain MRI. While most existing works try to improve detection accuracy by proposing new model structures or algorithms,

Externí odkaz: http://arxiv.org/abs/2408.08228

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Efficient Vision-Language Pre-training by Cluster Masking

Autor: Wei, Zihao, Pan, Zixuan, Owens, Andrew

We propose a simple strategy for masking image patches during visual-language contrastive learning that improves the quality of the learned representations and the training speed. During each iteration of training, we randomly mask clusters of visual

Externí odkaz: http://arxiv.org/abs/2405.08815

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TSB: Tiny Shared Block for Efficient DNN Deployment on NVCIM Accelerators

Autor: Qin, Yifan, Yan, Zheyu, Pan, Zixuan, Wen, Wujie, Hu, Xiaobo Sharon, Shi, Yiyu

Compute-in-memory (CIM) accelerators using non-volatile memory (NVM) devices offer promising solutions for energy-efficient and low-latency Deep Neural Network (DNN) inference execution. However, practical deployment is often hindered by the challeng

Externí odkaz: http://arxiv.org/abs/2406.06544

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Masked Diffusion as Self-supervised Representation Learner

Autor: Pan, Zixuan, Chen, Jianxu, Shi, Yiyu

Denoising diffusion probabilistic models have recently demonstrated state-of-the-art generative performance and have been used as strong pixel-level representation learners. This paper decomposes the interrelation between the generative capability an

Externí odkaz: http://arxiv.org/abs/2308.05695

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Discovering Intrinsic Reward with Contrastive Random Walk

Autor: Pan, Zixuan, Wei, Zihao, Huang, Yidong, Gupta, Aditya

The aim of this paper is to demonstrate the efficacy of using Contrastive Random Walk as a curiosity method to achieve faster convergence to the optimal policy.Contrastive Random Walk defines the transition matrix of a random walk with the help of ne

Externí odkaz: http://arxiv.org/abs/2204.10976

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