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Core-Periphery Principle Guided Redesign of Self-Attention in Transformers.

, , , , , , , , и . CoRR, (2023)

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Liu Liu

Liu Liu

Liu Liu

Xingyi Liu

Zhiguo Liu

 

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Novel approach of combining temporal segmentation results to the region-binding process for separating moving objects from still background., , и . VCIP, том 4067 из Proceedings of SPIE, стр. 1066-1075. SPIE, (2000)Neural Architecture Search for Optimizing Deep Belief Network Models of fMRI Data., , , , и . MMMI@MICCAI, том 11977 из Lecture Notes in Computer Science, стр. 26-34. Springer, (2019)A Novel fMRI Representation Learning Framework with GAN., , , , , , и . MLMI@MICCAI, том 12436 из Lecture Notes in Computer Science, стр. 21-29. Springer, (2020)ATVHUNTER: Reliable Version Detection of Third-Party Libraries for Vulnerability Identification in Android Applications., , , , , , и . ICSE, стр. 1695-1707. IEEE, (2021)Admission Probability Prediction of College Entrance Examination Based on Siamese Network., , , и . EITCE, стр. 352-355. ACM, (2022)Modeling Cognitive Processes via Multi-stage Consistent Functional Response Detection., , , , , , , и . MBIA, том 8159 из Lecture Notes in Computer Science, стр. 180-188. Springer, (2013)Neural Architecture Search for Optimization of Spatial-Temporal Brain Network Decomposition., , , , и . MICCAI (7), том 12267 из Lecture Notes in Computer Science, стр. 377-386. Springer, (2020)Latent source mining in FMRI data via deep neural network., , , , , , и . ISBI, стр. 638-641. IEEE, (2016)Multple-demand system identification and characterization via sparse representations of fMRI data., , , , и . ISBI, стр. 70-73. IEEE, (2016)Modeling 4D fMRI Data via Spatio-Temporal Convolutional Neural Networks (ST-CNN)., , , , , , , и . MICCAI (3), том 11072 из Lecture Notes in Computer Science, стр. 181-189. Springer, (2018)