Editorial: Understanding and bridging the gap between neuromorphic computing and machine learning, volume II.

IF 2.1 4区医学 Q2 MATHEMATICAL & COMPUTATIONAL BIOLOGY

Frontiers in Computational Neuroscience Pub Date : 2024-10-03 eCollection Date: 2024-01-01 DOI:10.3389/fncom.2024.1455530

Lei Deng, Huajin Tang, Kaushik Roy

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社论：理解和弥合神经形态计算与机器学习之间的差距》，第二卷。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Frontiers in Computational Neuroscience MATHEMATICAL & COMPUTATIONAL BIOLOGY-NEUROSCIENCES

CiteScore

5.30

自引率

3.10%

发文量

166

审稿时长

6-12 weeks

期刊介绍： Frontiers in Computational Neuroscience is a first-tier electronic journal devoted to promoting theoretical modeling of brain function and fostering interdisciplinary interactions between theoretical and experimental neuroscience. Progress in understanding the amazing capabilities of the brain is still limited, and we believe that it will only come with deep theoretical thinking and mutually stimulating cooperation between different disciplines and approaches. We therefore invite original contributions on a wide range of topics that present the fruits of such cooperation, or provide stimuli for future alliances. We aim to provide an interactive forum for cutting-edge theoretical studies of the nervous system, and for promulgating the best theoretical research to the broader neuroscience community. Models of all styles and at all levels are welcome, from biophysically motivated realistic simulations of neurons and synapses to high-level abstract models of inference and decision making. While the journal is primarily focused on theoretically based and driven research, we welcome experimental studies that validate and test theoretical conclusions. Also: comp neuro