Polynomial fitting algorithm based on neural network Y Tong, L Yu, S Li, J Liu, H Qin, W Li ASP Transactions on Pattern Recognition and Intelligent Systems 1 (1), 32-39, 2021 | 90 | 2021 |
Technology investigation on time series classification and prediction Y Tong, J Liu, L Yu, L Zhang, L Sun, W Li, X Ning, J Xu, H Qin, Q Cai PeerJ Computer Science 8, e982, 2022 | 23 | 2022 |
SNR: Symbolic network-based rectifiable learning framework for symbolic regression J Liu, W Li, L Yu, M Wu, L Sun, W Li, Y Li Neural Networks 165, 1021-1034, 2023 | 9 | 2023 |
Mmsr: Symbolic regression is a multimodal task Y Li, J Liu, W Li, L Yu, M Wu, W Li, M Hao, S Wei, Y Deng arXiv preprint arXiv:2402.18603, 2024 | 3 | 2024 |
Transcendental equation solver: A novel neural network for solving transcendental equation J Liu, G Wang, W Li, L Sun, L Zhang, L Yu Applied Soft Computing 117, 108425, 2022 | 3 | 2022 |
MMSR: Symbolic regression is a multi-modal information fusion task Y Li, J Liu, M Wu, L Yu, W Li, X Ning, W Li, M Hao, Y Deng, S Wei Information Fusion 114, 102681, 2025 | 2 | 2025 |
A dependency-based hybrid deep learning framework for target-dependent sentiment classification J Liu, S Li Pattern Recognition Letters 176, 160-166, 2023 | 2 | 2023 |
CaMo: Capturing the modularity by end-to-end models for Symbolic Regression J Liu, M Wu, L Yu, W Li, W Li, Y Li, M Hao, Y Deng, S Wei Knowledge-Based Systems 309, 112747, 2025 | 1 | 2025 |
Mathematical representation of 2D image boundary contour using fractional implicit polynomial Y Tong, L Yu, W Li, J Liu, M Wu, Y Yang Optoelectronics Letters 19 (4), 252-256, 2023 | 1 | 2023 |
Fitting objects with implicit polynomials by deep neural network J Liu, L Yu, L Sun, Y Tong, M Wu, W Li Optoelectronics Letters 19 (1), 60-64, 2023 | 1 | 2023 |
Producing monomial sets with lower calculation complexity for polynomial fitting J Liu, L Yu, M Wu, Y Tong, J Xu, Z Li, X Hu, W Li 2021 International Conference on High Performance Big Data and Intelligent …, 2021 | 1 | 2021 |
DN-CL: Deep Symbolic Regression against Noise via Contrastive Learning J Liu, Y Li, L Yu, M Wu, W Li, W Li, M Hao, Y Deng, S Wei arXiv preprint arXiv:2406.14844, 2024 | | 2024 |