Readership
Artificial Intelligence Researcher, Computational Biologists, Computer Scientists, Diagnosticians, Mental Health Specialists, Neurologists, Neuroscientists, Psychiatric Nurses, Psychiatrists, Psychologists, Psychotherapists
Scope
Neural Networks provides a forum for developing and nurturing an international community of scholars and practitioners who are interested in all aspects of neural networks, including deep learning and related approaches to artificial intelligence and machine learning. Neural Networks welcomes submissions that contribute to the full range of neural networks research, from cognitive modeling and computational neuroscience, through deep learning algorithms and mathematical analyses, to engineering and technological applications of systems that significantly use neural network concepts and learning techniques. This uniquely broad range facilitates the cross-fertilization of ideas between biological and technological studies, and helps to foster the development of the interdisciplinary community that is interested in biologically-inspired artificial intelligence. Accordingly, the Neural Networks editorial board represents experts in fields including psychology, neurobiology, computer science, engineering, mathematics, and physics. On the other hand, neural networks should be central to submissions. The journal publishes articles, letters, and reviews/tutorials, as well as letters to the editor, editorials, and current events. Articles are published in one of five sections: learning systems, cognitive science, neuroscience, mathematical and computational analysis, engineering and applications.
Neural Networks is the archival journal of three of the oldest and most prominent neural network societies: the International Neural Network Society (INNS), the Asia-Pacific Neural Network Society (APNNS), and the Japanese Neural Network Society (JNNS). A subscription to the journal is included with membership in each of these societies.
Sponsoring Association(s)
Asia Pacific Neural Network Society (APNNS), International Neural Network Society (INNS), Japanese Neural Network Society (JNNS)