Zobrazeno 1 - 7
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pro vyhledávání: '"Yu, Yueyao"'
Autor:
Yu, Yueyao, Zhang, Yin
Since its introduction in 2017, Transformer has emerged as the leading neural network architecture, catalyzing revolutionary advancements in many AI disciplines. The key innovation in Transformer is a Self-Attention (SA) mechanism designed to capture
Externí odkaz:
http://arxiv.org/abs/2312.06182
We solve a fundamental challenge in semiconductor IC design: the fast and accurate characterization of nanoscale photonic devices. Much like the fusion between AI and EDA, many efforts have been made to apply DNNs such as convolutional neural network
Externí odkaz:
http://arxiv.org/abs/2205.09045
Autor:
Yu, Yueyao, Zhang, Yin
To enhance resource efficiency and model deployability of neural networks, we propose a neural-layer architecture based on Householder weighting and absolute-value activating, called Householder-absolute neural layer or simply Han-layer. Compared to
Externí odkaz:
http://arxiv.org/abs/2106.04088
Autor:
Yu, Yueyao, Zhang, Yin
Despite the tremendous successes of deep neural networks (DNNs) in various applications, many fundamental aspects of deep learning remain incompletely understood, including DNN trainability. In a trainability study, one aims to discern what makes one
Externí odkaz:
http://arxiv.org/abs/2105.08911
Deep learning models are vulnerable to adversarial examples, which poses an indisputable threat to their applications. However, recent studies observe gradient-masking defenses are self-deceiving methods if an attacker can realize this defense. In th
Externí odkaz:
http://arxiv.org/abs/1902.06415
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