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Neural pathways as model explanations consist of a sparse set of neurons that provide the same level of prediction performance as the whole model. Existing methods primarily focus on accuracy and sparsity but the generated pathways may offer limited
Externí odkaz:
http://arxiv.org/abs/2309.09887
The popular VQ-VAE models reconstruct images through learning a discrete codebook but suffer from a significant issue in the rapid quality degradation of image reconstruction as the compression rate rises. One major reason is that a higher compressio
Externí odkaz:
http://arxiv.org/abs/2305.02541
In many applications, it is essential to understand why a machine learning model makes the decisions it does, but this is inhibited by the black-box nature of state-of-the-art neural networks. Because of this, increasing attention has been paid to ex
Externí odkaz:
http://arxiv.org/abs/2111.01215
Akademický článek
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Akademický článek
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Autor:
Cai JQ; Department of Pharmacy, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou University Affiliated Provincial Hospital, Fuzhou, Fujian, China., Wang YM; School of Pharmacy, Fujian University of Traditional Chinese Medicine, Department of Pharmacy, Fuzhou, Fujian, China., Lin X; School of Pharmacy, Fujian Medical University, Fuzhou, Fujian, China., Xie M; Department of Pharmacy, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou University Affiliated Provincial Hospital, Fuzhou, Fujian, China., Zhang G; Department of Oncology, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou, Fujian, China., Wei XX; Department of Pharmacy, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou University Affiliated Provincial Hospital, Fuzhou, Fujian, China., Sun H; Department of Pharmacy, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou University Affiliated Provincial Hospital, Fuzhou, Fujian, China.
Publikováno v:
Future oncology (London, England) [Future Oncol] 2024 Oct 14, pp. 1-11. Date of Electronic Publication: 2024 Oct 14.
