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Innovative Distributed Maintenance Concept
| 順位 | タイトル | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| 著者 | 雑誌 | 巻 | 号 | ページ | 年 | PKVアクセス数 | |||
| 461 | Neural Information Processing and Computations of Two-Input Synapses | ||||||||
| Soon Ho Kim, Junhyuk Woo, Kiri Choi, MooYoung Choi, Kyungreem Han | Neural Computation | 34 | 10 | 2102–2131 | 2022 | 31.94 | |||
| 平均評価: / 5 ( 件のレビュー) | |||||||||
| 462 | NIR-Prompt: A Multi-task Generalized Neural Information Retrieval Training Framework | ||||||||
| Shicheng Xu, Liang Pang, Huawei Shen, Xueqi Cheng | ACM Transactions on Information Systems | 42 | 2 | 1–32 | 2023 | 31.9 | |||
| 平均評価: / 5 ( 件のレビュー) | |||||||||
| 463 | A Novel Nonparametric Approach for Neural Encoding and Decoding Models of Multimodal Receptive Fields | ||||||||
| Rahul Agarwal, Zhe Chen, Fabian Kloosterman, Matthew A. Wilson, Sridevi V. Sarma | Neural Computation | 28 | 7 | 1356–1387 | 2016 | 31.87 | |||
| 平均評価: / 5 ( 件のレビュー) | |||||||||
| 464 | Presynaptic Spontaneous Activity Enhances the Accuracy of Latency Coding | ||||||||
| Marie Levakova, Massimiliano Tamborrino, Lubomir Kostal, Petr Lansky | Neural Computation | 28 | 10 | 2162–2180 | 2016 | 31.84 | |||
| 平均評価: / 5 ( 件のレビュー) | |||||||||
| 465 | Online Learning Based on Online DCA and Application to Online Classification | ||||||||
| Hoai An Le Thi, Vinh Thanh Ho | Neural Computation | 32 | 4 | 759–793 | 2020 | 31.8 | |||
| 平均評価: / 5 ( 件のレビュー) | |||||||||
| 466 | Neural Mechanism to Simulate a Scale-Invariant Future | ||||||||
| Karthik H. Shankar, Inder Singh, Marc W. Howard | Neural Computation | 28 | 12 | 2594–2627 | 2016 | 31.79 | |||
| 平均評価: / 5 ( 件のレビュー) | |||||||||
| 467 | Neural Circuits for Dynamics-Based Segmentation of Time Series | ||||||||
| Tiberiu Teşileanu, Siavash Golkar, Samaneh Nasiri, Anirvan M. Sengupta, Dmitri B. Chklovskii | Neural Computation | 34 | 4 | 891–938 | 2022 | 31.78 | |||
| 平均評価: / 5 ( 件のレビュー) | |||||||||
| 468 | Effect of Morphologic Features of Neurons on the Extracellular Electric Potential: A Simulation Study Using Cable Theory and Electro-Quasi-Static Equations | ||||||||
| R. Bestel, R. Appali, U. van Rienen, C. Thielemann | Neural Computation | 29 | 11 | 2955–2978 | 2017 | 31.78 | |||
| 平均評価: / 5 ( 件のレビュー) | |||||||||
| 469 | Learning Rates for Classification with Gaussian Kernels | ||||||||
| Shao-Bo Lin, Jinshan Zeng, Xiangyu Chang | Neural Computation | 29 | 12 | 3353–3380 | 2017 | 31.76 | |||
| 平均評価: / 5 ( 件のレビュー) | |||||||||
| 470 | Autonomous Learning With High-Dimensional Computing Architecture Similar to Von Neumann’s | ||||||||
| Pentti Kanerva | Neural Computation | 38 | 7 | 1117–1134 | 2026 | 31.74 | |||
| 平均評価: / 5 ( 件のレビュー) | |||||||||