aug 18, 2023 under review 分享六: 研究方向:人工智能 投稿结果:未知 投稿时间节点: 7.25 投稿 7.26 with editor 8.20 还是with editor 投稿总结 《Neural Networks》中科院计算机科学大类二区TOP期刊。根据网友经验分享,作为TOP期刊,此期刊对论文具有一定的质量要求,编辑和审稿人看文章很仔细,提出的意见专业且诚恳...
小佩了解到,神经网络领域SCI期刊:NEURAL NETWORKS,最新影响因子9+,自引率7.7%。 NEURAL NETWORKS旨在发展和培养一个国际论坛,使对神经网络所有方面感兴趣的学者和从业者可以充分展开包括深度学习人工智能和机器的相关方法。 01 基本信息 期刊名称:NEURAL NETWORKS; 期刊ISSN:0893-6080; 出版地区:ENGLAND; 出版商:Elsevie...
去年投出一个月后under review,又过四个月一审被拒,好慢啊! 两个审稿人,一个不看实际创新,只说应该做大规模的,TMD! 另一个指出一些问题,但看得也不仔细,有个参数我明明写上了,愣是说找不到。大概我当时把初版写得难懂,人家不愿意看吧。 这期刊越办越垃圾了还是越来越偏应用了? 研究方向: 信息科学 ...
Neural Networks is the archival journal of the world's three oldest neural modeling societies: the International Neural Network Society (INNS), the European Neural Network Society (ENNS), and the Japanese Neural Network Society (JNNS). A subscription to the journal is included with membership in...
论文被Neural Networks录用，狂喜，散一半金币638个，同时为还在审稿的6篇文章祈福，希望能被顺利接受 ...
Under these conditions, it is possible that the networks are overfitting the data, explaining the very high classification rates, and that the technique would not generalise well. Leeming [32] performs a similar investigation solely using an MLP back propagation network which was trained in two ...
2. Neural Networks as Relational Graphs To explore the graph structure of neural networks, we first introduce the concept of our relational graph representation and its instantiations. We demonstrate how our representation can capture diverse neural network architectures under a unified framework. Using ...
2. Neural Networks as Relational Graphs To explore the graph structure of neural networks, we first introduce the concept of our relational graph representation and its instantiations. We demonstrate how our representation can capture diverse neural network architectures under a unified framework. Using ...
Original, full-length articles are considered with the understanding that they have not been published except in abstract form and are not concurrently under review elsewhere. Authors are welcome, but not required, to suggest reviewers. Authors need to specify one of the five Sections: Cognitive Sc...
The remarkable performance of overparameterized deep neural networks (DNNs) must arise from an interplay between network architecture, training algorithms, and structure in the data. To disentangle these three components for supervised learning, we apply a Bayesian picture based on the functions expressed...