IEEE TNNLS

Theoretical Exploration of Flexible Transmitter Model

Jin-Hui Wu, Shao-Qun Zhang, Yuan Jiang, Zhi-Hua Zhou

Comments 45 pages, to be published in IEEE Transactions on Neural Networks and Learning Systems (TNNLS)

LaplaceNet: A Hybrid Graph-Energy Neural Network for Deep Semi-Supervised Classification

Philip Sellars, Angelica I. Aviles-Rivero, Carola-Bibiane Schönlieb

Comments https://ieeexplore.ieee.org/document/9900300

Journal ref IEEE Transactions on Neural Networks and Learning Systems 2022

Tensor-CSPNet: A Novel Geometric Deep Learning Framework for Motor Imagery Classification

Ce Ju, Cuntai Guan

Comments 15 pages, 10 figures, 12 tables; This work has been accepted by the IEEE Transactions on Neural Networks and Learning Systems. Copyright will be transferred without notice, after which this version may no longer be accessible

Partial sequence labeling with structured Gaussian Processes

Xiaolei Lu, Tommy W. S. Chow

Journal ref IEEE Transactions on Neural Networks and Learning Systems, 2022, 1 - 10

Few-Shot Object Detection: A Comprehensive Survey

Mona Köhler, Markus Eisenbach, Horst-Michael Gross

Comments 27 pages, 13 figures, submitted to IEEE Transactions on Neural Networks and Learning Systems

LipSound2: Self-Supervised Pre-Training for Lip-to-Speech Reconstruction and Lip Reading

Leyuan Qu, Cornelius Weber, Stefan Wermter

Comments ACCEPTED IN IEEE Transactions on Neural Networks and Learning Systems

Fuzzy Attention Neural Network to Tackle Discontinuity in Airway Segmentation

Yang Nan, Javier Del Ser, Zeyu Tang, Peng Tang, Xiaodan Xing, Yingying Fang, Francisco Herrera, Witold Pedrycz, Simon Walsh, Guang Yang

Comments 12 pages, 5 figures, Submitted to IEEE TNNLS

Autonomous Cross Domain Adaptation under Extreme Label Scarcity

Weiwei Weng, Mahardhika Pratama, Choiru Za'in, Marcus De Carvalho, Rakaraddi Appan, Andri Ashfahani, Edward Yapp Kien Yee

Journal ref IEEE Transactions on Neural Networks and Learning Systems, 2022

Catastrophic Interference in Reinforcement Learning: A Solution Based on Context Division and Knowledge Distillation

Tiantian Zhang, Xueqian Wang, Bin Liang, Bo Yuan

Comments 21 pages

Journal ref IEEE Transactions on Neural Networks and Learning Systems, 2022

Cellular Automata Can Reduce Memory Requirements of Collective-State Computing

Denis Kleyko, E. Paxon Frady, Friedrich T. Sommer

Comments 13 pages, 11 figures

Journal ref IEEE Transactions on Neural Networks and Learning Systems, vol. 32, no. 6, 2022

Density Encoding Enables Resource-Efficient Randomly Connected Neural Networks

Denis Kleyko, Mansour Kheffache, E. Paxon Frady, Urban Wiklund, Evgeny Osipov

Comments 7 pages, 7 figures

Journal ref IEEE Transactions on Neural Networks and Learning Systems (2021), vol. 32, no. 8

Integer Echo State Networks: Efficient Reservoir Computing for Digital Hardware

Denis Kleyko, E. Paxon Frady, Mansour Kheffache, Evgeny Osipov

Comments 13 pages, 11 figures, 5 tables

Journal ref IEEE Transactions on Neural Networks and Learning Systems, vol. 33, no. 4, 2022

Fusing Higher-order Features in Graph Neural Networks for Skeleton-based Action Recognition

Zhenyue Qin, Yang Liu, Pan Ji, Dongwoo Kim, Lei Wang, Bob McKay, Saeed Anwar, Tom Gedeon

Comments Accepted by IEEE Transactions on Neural Networks and Learning Systems

Subtype-Aware Dynamic Unsupervised Domain Adaptation

Xiaofeng Liu, Fangxu Xing, Jia You, Jun Lu, C. -C. Jay Kuo, Georges El Fakhri, Jonghye Woo

Comments IEEE Transactions on Neural Networks and Learning Systems (TNNLS)

Low-complexity Approximate Convolutional Neural Networks

R. J. Cintra, S. Duffner, C. Garcia, A. Leite

Comments 13 pages, 4 figures, 8 tables

Journal ref IEEE Transactions on Neural Networks and Learning Systems, v. 29, n. 12, Dec. 2018

Prototypical Graph Contrastive Learning

Shuai Lin, Pan Zhou, Zi-Yuan Hu, Shuojia Wang, Ruihui Zhao, Yefeng Zheng, Liang Lin, Eric Xing, Xiaodan Liang

Comments To appear in TNNLS 2022

Knowledge Distillation Using Hierarchical Self-Supervision Augmented Distribution

Chuanguang Yang, Zhulin An, Linhang Cai, Yongjun Xu

Comments 15 pages, Accepted by IEEE Transactions on Neural Networks and Learning Systems 2022

Comprehensive Graph Gradual Pruning for Sparse Training in Graph Neural Networks

Chuang Liu, Xueqi Ma, Yibing Zhan, Liang Ding, Dapeng Tao, Bo Du, Wenbin Hu, Danilo Mandic

Comments 29 pages, 27 figures, submitting to IEEE TNNLS

Self-supervised Autoregressive Domain Adaptation for Time Series Data

Mohamed Ragab, Emadeldeen Eldele, Zhenghua Chen, Min Wu, Chee-Keong Kwoh, Xiaoli Li

Comments Accepted for publication in IEEE Transactions on Neural Networks and Learning Systems

ACERAC: Efficient reinforcement learning in fine time discretization

Jakub Łyskawa, Paweł Wawrzyński

Comments Submitted to IEEE Transactions on Neural Networks and Learning Systems. arXiv admin note: text overlap with arXiv:2009.04777

SSFG: Stochastically Scaling Features and Gradients for Regularizing Graph Convolutional Networks

Haimin Zhang, Min Xu, Guoqiang Zhang, Kenta Niwa

Journal ref IEEE Transactions on Neural Networks and Learning Systems, 2022

Cardiomegaly Detection using Deep Convolutional Neural Network with U-Net

Soham S. Sarpotdar

Comments 8 pages, 7 figures, submitted in the IEEE Transactions on Neural Networks and Learning Systems(IEEE TNNLS)

Event-based Motion Segmentation with Spatio-Temporal Graph Cuts

Yi Zhou, Guillermo Gallego, Xiuyuan Lu, Siqi Liu, Shaojie Shen

Journal ref IEEE Transactions on Neural Networks and Learning Systems, 2021

Graph Neural Networks for Graph Drawing

Matteo Tiezzi, Gabriele Ciravegna, Marco Gori

Comments Accepted for publication in IEEE Transaction of Neural Networks and Learning Systems (TNNLS) 2022, Special Issue on Deep Neural Networks for Graphs: Theory, Models, Algorithms and Applications

Compressing Features for Learning with Noisy Labels

Yingyi Chen, Shell Xu Hu, Xi Shen, Chunrong Ai, Johan A. K. Suykens

Comments Accepted to TNNLS 2022. Project page: https://yingyichen-cyy.github.io/CompressFeatNoisyLabels/

Adaptive Neural Network Stochastic-Filter-based Controller for Attitude Tracking with Disturbance Rejection

Hashim A. Hashim, Kyriakos G. Vamvoudakis

Comments IEEE Transactions on Neural Networks and Learning Systems

TraverseNet: Unifying Space and Time in Message Passing for Traffic Forecasting

Zonghan Wu, Da Zheng, Shirui Pan, Quan Gan, Guodong Long, George Karypis

Comments 10 pages

Journal ref IEEE transactions on neural networks and learning systems. 2022

InfoAT: Improving Adversarial Training Using the Information Bottleneck Principle

Mengting Xu, Tao Zhang, Zhongnian Li, Daoqiang Zhang

Comments Published in: IEEE Transactions on Neural Networks and Learning Systems ( Early Access )

Shilling Black-box Recommender Systems by Learning to Generate Fake User Profiles

Chen Lin, Si Chen, Meifang Zeng, Sheng Zhang, Min Gao, Hui Li

Comments Accepted by TNNLS. 15 pages, 8 figures

Significance tests of feature relevance for a black-box learner

Ben Dai, Xiaotong Shen, Wei Pan

Comments Accepted for publication in IEEE Transactions on Neural Networks and Learning Systems

Journal ref IEEE Transactions on Neural Networks and Learning Systems, 2022