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Titlebook: Neural Information Processing; 30th International C Biao Luo,Long Cheng,Chaojie Li Conference proceedings 2024 The Editor(s) (if applicable

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發(fā)表于 2025-3-21 17:06:49 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Neural Information Processing
副標(biāo)題30th International C
編輯Biao Luo,Long Cheng,Chaojie Li
視頻videohttp://file.papertrans.cn/664/663573/663573.mp4
叢書名稱Communications in Computer and Information Science
圖書封面Titlebook: Neural Information Processing; 30th International C Biao Luo,Long Cheng,Chaojie Li Conference proceedings 2024 The Editor(s) (if applicable
描述The nine-volume set constitutes the refereed proceedings of the 30th International Conference on Neural Information Processing, ICONIP 2023, held in Changsha, China, in November 2023.??.The?1274?papers presented in the proceedings set were carefully reviewed and selected from?652?submissions.?.The ICONIP conference aims to provide a leading international forum for researchers, scientists, and industry professionals who are working in neuroscience, neural networks, deep learning, and related fields to share their new ideas, progress, and achievements..
出版日期Conference proceedings 2024
關(guān)鍵詞Bioinformatics; Brain-machine interface; Computational finance; Computational intelligence; Control and
版次1
doihttps://doi.org/10.1007/978-981-99-8132-8
isbn_softcover978-981-99-8131-1
isbn_ebook978-981-99-8132-8Series ISSN 1865-0929 Series E-ISSN 1865-0937
issn_series 1865-0929
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
The information of publication is updating

書目名稱Neural Information Processing影響因子(影響力)




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書目名稱Neural Information Processing網(wǎng)絡(luò)公開度學(xué)科排名




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o complementary paradigms: under-approximation (or animation-based) and over-approximation (or proof-based). We applied these paradigms in order to produce behavioural state/chart views from B models and we carried out an empirical study to assess the quality and relevance of these graphical represe
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Shuxiao Song,Xiao Yu,Yuexuan Ma,Jiale Li,Jie Yuve logic programming for learning repairs to system components while ensuring no new errors are introduced and interactions with other components are maintained. These two phases are iterated until a correct specification is reached, enabling rigorous and scalable support for automated analysis and
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Xiaohan Zhou,Yuzhe Liu,Wei Sun,Qiang Yuso quickly identifies unsafe models. As a bonus, it adds testing capabilities to Cubicle, such as the ability to detect deadlocks..Our first experiments have yielded promising results. CFL effectively allows Cubicle to generate crucial invariants, useful to handle hierarchical systems, while also be
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Jiaji Qin,Chao Gao,Dingkun Wangrmalized as an interface automaton. Following common practice in network programming, our vertical contract uses an asynchronous atomic callback (AAC) pattern. The formal composition of these interface automata allows us to reason about the combination of a timed actor model and the AAC pattern, ena
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Wenchang Zhang,Kaiqiang Zhang,Linling Jiang,Fan Zhangrmalized as an interface automaton. Following common practice in network programming, our vertical contract uses an asynchronous atomic callback (AAC) pattern. The formal composition of these interface automata allows us to reason about the combination of a timed actor model and the AAC pattern, ena
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