📰 Neural Networks 2018 — papers

The works of Neural Networks published in 2018 that our library holds (publisher: Elsevier BV): 1 work, listed below with the most cited first; each has a page with our summary, its key points and its references.

Most cited papers

By their OpenAlex citations; a paper with our summary links to its page here, the others to the original.

1. A systematic study of the class imbalance problem in convolutional neural networks ↗Mateusz Buda, Atsuto Maki, Maciej A. Mazurowski3,045 citations
2. Sigmoid-weighted linear units for neural network function approximation in reinforcement learning ↗Stefan Elfwing, Eiji Uchibe, Kenji Doya2,086 citations
3. Deep learning in spiking neural networks ↗Amirhossein Tavanaei, Masoud Ghodrati, Saeed Reza Kheradpisheh et al.1,386 citations
4. Convolutional neural networks for seizure prediction using intracranial and scalp electroencephalogram ↗Nhan Duy Truong, Anh Duy Nguyen, Levin Kuhlmann et al.635 citations
5. Optimal approximation of piecewise smooth functions using deep ReLU neural networks ↗Philipp Petersen, Felix Voigtlaender432 citations
6. A comparison of deep networks with ReLU activation function and linear spline-type methods ↗Konstantin Eckle, Johannes Schmidt-Hieber409 citations
7. An extensive experimental survey of regression methods ↗Manuel Fernández-Delgado, Manisha Sanjay Sirsat, Eva Cernadas et al.377 citations
8. Soft + Hardwired attention: An LSTM framework for human trajectory prediction and abnormal event detection ↗Tharindu Fernando, Simon Denman, Sridha Sridharan et al.371 citations
9. DGCNN: A convolutional neural network over large-scale labeled graphs ↗Anh Viet Phan, Le-Minh Nguyen, Yen Lam Hoang Nguyen et al.355 citations
10. State representation learning for control: An overview ↗Timothée Lesort, Natalia Díaz-Rodríguez, Jean-François Goudou et al.301 citations

All works of the year (219)

The most cited first; 1 with our summary link to their page here, the others to the original.

1. A systematic study of the class imbalance problem in convolutional neural networks ↗Mateusz Buda, Atsuto Maki, Maciej A. Mazurowski3,045 citations
2. Sigmoid-weighted linear units for neural network function approximation in reinforcement learning ↗Stefan Elfwing, Eiji Uchibe, Kenji Doya2,086 citations
3. Deep learning in spiking neural networks ↗Amirhossein Tavanaei, Masoud Ghodrati, Saeed Reza Kheradpisheh et al.1,386 citations
4. Convolutional neural networks for seizure prediction using intracranial and scalp electroencephalogram ↗Nhan Duy Truong, Anh Duy Nguyen, Levin Kuhlmann et al.635 citations
5. Optimal approximation of piecewise smooth functions using deep ReLU neural networks ↗Philipp Petersen, Felix Voigtlaender432 citations
6. A comparison of deep networks with ReLU activation function and linear spline-type methods ↗Konstantin Eckle, Johannes Schmidt-Hieber409 citations
7. An extensive experimental survey of regression methods ↗Manuel Fernández-Delgado, Manisha Sanjay Sirsat, Eva Cernadas et al.377 citations
8. Soft + Hardwired attention: An LSTM framework for human trajectory prediction and abnormal event detection ↗Tharindu Fernando, Simon Denman, Sridha Sridharan et al.371 citations
9. DGCNN: A convolutional neural network over large-scale labeled graphs ↗Anh Viet Phan, Le-Minh Nguyen, Yen Lam Hoang Nguyen et al.355 citations
10. State representation learning for control: An overview ↗Timothée Lesort, Natalia Díaz-Rodríguez, Jean-François Goudou et al.301 citations
11. Echo state networks are universal ↗Lyudmila Grigoryeva, Juan‐Pablo Ortega274 citations
12. Design of deep echo state networks ↗Claudio Gallicchio, Alessio Micheli, Luca Pedrelli262 citations
13. Deep neural network for traffic sign recognition systems: An analysis of spatial transformers and stochastic optimisation methods ↗Álvaro Arcos García, Juan A. Álvarez-García, Luis Miguel Soria Morillo244 citations
14. Inter-class sparsity based discriminative least square regression ↗Jie Wen, Yong Dong Xu, Yong Dong Xu et al.219 citations
15. Quasi-projective synchronization of fractional-order complex-valued recurrent neural networks ↗Shuai Yang, Juan Yu, Cheng Hu et al.170 citations
16. Spiking neural networks for handwritten digit recognition—Supervised learning and network optimization ↗Shruti Kulkarni, Bipin Rajendran161 citations
17. Fixed-time synchronization of inertial memristor-based neural networks with discrete delay ↗Chuan Chen, Lixiang Li, Haipeng Peng et al.152 citations
18. Low-rank representation with adaptive graph regularization ↗Jie Wen, Xiaozhao Fang, Yong Dong Xu et al.148 citations
19. Towards correlation-based time window selection method for motor imagery BCIs ↗Jiankui Feng, Erwei Yin, Jing Jin et al.143 citations
20. GXNOR-Net: Training deep neural networks with ternary weights and activations without full-precision memory under a unified discretization framework ↗Lei Deng, Peng Jiao, Jing Pei et al.142 citations
21. Effective neural network training with adaptive learning rate based on training loss ↗Tomoumi Takase, Satoshi Oyama, Masahito Kurihara140 citations
22. Finite-time synchronization of stochastic coupled neural networks subject to Markovian switching and input saturation ↗Palanisamy Selvaraj, Rathinasamy Sakthivel, Oh‐Min Kwon138 citations
23. Global Mittag-Leffler stability and synchronization analysis of fractional-order quaternion-valued neural networks with linear threshold neurons ↗Xujun Yang, Chuandong Li, Qiankun Song et al.138 citations
24. Biased Dropout and Crossmap Dropout: Learning towards effective Dropout regularization in convolutional neural network ↗Alvin Poernomo, Dae-Ki Kang137 citations
25. Response prediction of nonlinear hysteretic systems by deep neural networks ↗Taeyong Kim, Oh‐Sung Kwon, Junho Song132 citations

See all 219 papers in Neural Networks 2018 — papers →

📄 Works with our summary in our library (1)

The most cited first (OpenAlex citations plus our library's).

1. Continual Lifelong Learning with Neural Networks: A ReviewNeural NetworksGerman I. Parisi, Ronald Kemker, Jose L. Part, et al.2018 · 3,224 citations

📚 Fields

🖥️Computer Science (1)

🧑‍🔬 Top authors

Authors with a page who published here most often: their works here, and the citations of those works.

🏛️ Top institutions

Institutions on the bylines of its works here, by the number of works.

🎓Rochester Institute of TechnologyRochester · United States1 work here🎓Universität HamburgHamburg · Germany1 work here🎓Heriot-Watt UniversityEdinburgh · United Kingdom1 work here

works and citations from OpenAlex and our library.

↑ back to top

This page in Markdown → https://md.research.elamur.ai/free/en/venues/neural-networks/2018/