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Neural Networks, Volume 146
Volume 146, February 2022
- Yun Yang
, Yulong Rao, Minghao Yu, Yan Kang
:
Multi-layer information fusion based on graph convolutional network for knowledge-driven herb recommendation. 1-10 - Santosh Kumar Yadav
, Siva Sai
, Akshay Gundewar
, Heena Rathore
, Kamlesh Tiwari
, Hari Mohan Pandey
, Mohit Mathur:
CSITime: Privacy-preserving human activity recognition using WiFi channel state information. 11-21 - M. Yunus Seker
, Alper Ahmetoglu
, Yukie Nagai
, Minoru Asada, Erhan Öztop
, Emre Ugur
:
Imitation and mirror systems in robots through Deep Modality Blending Networks. 22-35
- Chahat Raj
, Priyanka Meel:
ARCNN framework for multimodal infodemic detection. 36-68
- Yingjie Tian
, Shiding Sun
, Jingjing Tang
:
Multi-view Teacher-Student Network. 69-84
- Qiang Li
:
Functional connectivity inference from fMRI data using multivariate information measures. 85-97 - Chentao Xu, Qingshan Liu
:
An inertial neural network approach for robust time-of-arrival localization considering clock asynchronization. 98-106
- Xinya Wang
, Jiayi Ma
, Junjun Jiang, Xiao-Ping Zhang
:
Dilated projection correction network based on autoencoder for hyperspectral image super-resolution. 107-119
- Zhi Chang, Dexin Zhao, Huilin Chen, Jingdan Li, Pengfei Liu:
Event-centric multi-modal fusion method for dense video captioning. 120-129
- Dawid Polap
, Marcin Wozniak
:
A hybridization of distributed policy and heuristic augmentation for improving federated learning approach. 130-140
- Seung-Hoon Lee
, Myeong-Jin Park, Daehyun Ji, O. M. Kwon
:
Stability and dissipativity criteria for neural networks with time-varying delays via an augmented zero equality approach. 141-150 - Nadezhda Semenova
, Laurent Larger
, Daniel Brunner
:
Understanding and mitigating noise in trained deep neural networks. 151-160 - Xinrui Jiang, Sitian Qin, Xiaoping Xue
, Xinzhi Liu
:
A second-order accelerated neurodynamic approach for distributed convex optimization. 161-173
- Najmeh Ziraki, Fadi Dornaika
, Alireza Bosaghzadeh
:
Multiple-view flexible semi-supervised classification through consistent graph construction and label propagation. 174-180
- Sindre Stenen Blakseth
, Adil Rasheed
, Trond Kvamsdal, Omer San
:
Deep neural network enabled corrective source term approach to hybrid analysis and modeling. 181-199 - Gregory P. Davis
, Garrett E. Katz
, Rodolphe J. Gentili, James A. Reggia:
NeuroLISP: High-level symbolic programming with attractor neural networks. 200-219
- Kateryna Chumachenko, Alexandros Iosifidis, Moncef Gabbouj
:
Feedforward neural networks initialization based on discriminant learning. 220-229 - Enzo Tartaglione
, Andrea Bragagnolo
, Attilio Fiandrotti, Marco Grangetto:
LOss-Based SensiTivity rEgulaRization: Towards deep sparse neural networks. 230-237 - Miguel Vasco
, Hang Yin
, Francisco S. Melo
, Ana Paiva:
Leveraging hierarchy in multimodal generative models for effective cross-modality inference. 238-255
- Pieter Verbeke
, Tom Verguts
:
Using top-down modulation to optimally balance shared versus separated task representations. 256-271
- Nicholas Geneva
, Nicholas Zabaras
:
Transformers for modeling physical systems. 272-289
- Ben Yang
, Xuetao Zhang
, Badong Chen
, Feiping Nie, Zhiping Lin
, Zhixiong Nan
:
Efficient correntropy-based multi-view clustering with anchor graph embedding. 290-302 - Chihiro Watanabe, Taiji Suzuki:
Deep two-way matrix reordering for relational data analysis. 303-315
- Niceto R. Luque
, Francisco Naveros
, Denis Sheynikhovich
, Eduardo Ros, Angelo Arleo
:
Computational epidemiology study of homeostatic compensation during sensorimotor aging. 316-333 - Ali Abdul Nabi Ali
, Mesbah Alam
, Simon C. Klein
, Nicolai Behmann
, Joachim K. Krauss
, Theodor Doll
, Holger Blume
, Kerstin Schwabe:
Predictive accuracy of CNN for cortical oscillatory activity in an acute rat model of parkinsonism. 334-340
- Wanlu Wei, Juan Yu, Leimin Wang
, Cheng Hu
, Haijun Jiang:
Fixed/Preassigned-time synchronization of quaternion-valued neural networks via pure power-law control. 341-349
- Enmei Tu, Zihao Wang, Jie Yang, Nikola K. Kasabov
:
Deep semi-supervised learning via dynamic anchor graph embedding in latent space. 350-360
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