论文
| • Zhang, T.*，Cheng, X., Jia, S., Chengyu T. Li, Poo, M., & Xu, B.* (2023) A brain-inspired algorithm that mitigates catastrophic forgetting of artificial and spiking neural networks with low computational cost. Science Advances 9: eadi2947. |
| • Zhang, T.*，Wang, Q., & Xu, B.* (2023) Self-Lateral Propagation Elevates Synaptic Modifications in Spiking Neural Networks for the Efficient Spatial and Temporal Classification. IEEE transactions on neural networks and learning systems : PP. |
| • Zhao, X., Zhang, D., Han, L., Zhang, T.*& Xu, B. (2023) ODE-based Recurrent Model-free Reinforcement Learning for POMDPs. Thirty-seventh Conference on Neural Information Processing Systems : : PP. |
| • Wei, Q., Han, L., & Zhang, T.* (2023) Learning and Controlling Multiscale Dynamics in Spiking Neural Networks Using Recursive Least Square Modifications. IEEE Transactions on Cybernetics : PP. |
| • Wang, Q., Zhang, T.*, Han, M., Wang, Y., & Xu, B. (2023) Complex Dynamic Neurons Improved Spiking Transformer Network for Efficient Automatic Speech Recognition. Thirty-Seventh AAAI Conference on Artificial Intelligence 37: 102-109. |
| • Zhang, D., Zhang, T.#*, Jia, S., Wang, Q., & Xu, B. (2023) Tuning Synaptic Connections instead of Weights by Genetic Algorithm in Spiking Policy Network. Machine Intelligence Research. : |
| • Zhang, D.#,Zhang, T.#*，Jia, S., & Xu, B.* (2022) Multiscale Dynamic Coding improved Spiking Actor Networkfor Reinforcement Learning. Thirty-Sixth AAAI Conference on Artificial Intelligence 36: 59-67. |
| • 张笃振, 程翔, 王岩松, 张新贺, 张铁林.*, 杜久林*, 徐波*. (2023) 生物结构启发基本网络算子助力类脑智能研究 人工智能. : |
| • 张铁林*, 李澄宇, 王刚, 张马路, 余磊, 徐波. (2023) 适合类脑脉冲神经网络的应用任务范式分析与展望, Research Advances and Perspectives of New Paradigms for Biology-inspired Spiking Neural Networks. 电子与信息学报, Journal of Electronics and Information Technology 45: 2675-2688. |
| • Li, X., Ni, Z., Ruan, J., Meng, L., Shi, J., Zhang, T.*, & Xu, B.* (2023) Mixture of personality improved Spiking actor network for efficient multi-agent cooperation. Frontiers in Neuroscience 17: 1219405. |
| • Jia, S., Zhang, T.*, Zuo, R. & Xu, B.* (2023) Motif-topology improved Spiking Neural Network for Explaining Cocktail Party Effect and McGurk Effect. Frontiers in Neuroscience : PP. |
| • Jiang, Z., Xu, J.,Zhang, T., Poo, M.*, & Xu, B.* (2023) Origin of the efficiency of spike timing-based neural computation for processing temporal information. Neural Networks 160: 84-96. |
| • Cheng, X., Zhang, T.**, Jia, S., & Xu, B. (2022) Meta neurons improve spiking neural networks for efficient spatio-temporal learning. NeuroComputing 531: 217-225. |
| • Xing, D., Yang, Y.,Zhang, T., & Xu, B. (2022) A Brain-Inspired Approach for Probabilistic Estimation and Efficient Planning in Precision Physical Interaction. IEEE Transactions on Cybernetics : |
| • Jia, S.#, Zuo, R.#, Zhang, T.#*, Liu, H., & Xu, B.* (2022) Motif-topology and Reward-learning improved Spiking Neural Network for Efficient Multi-sensory Integration. Frontiers in Neuroscience : 8917-8921. |
| • Han, X., Jia, K.*, & Zhang, T.* (2022) Mouse-Brain Topology improved Evolutionary Neural Network for Efficient Reinforcement Learning. International Conference on Intelligence Science : 3-10. |
| • Cheng, X., Han, X., Song, Y., Zhang, T.*, & Xu, B.* (2022) Artificial Neural Network-assisted Amplitude Thresholding Improves Spike Detection. The 11th International Conference on Computing and Pattern Recognition : 465-470. |
| • Zhang, T., Cheng, X., Jia, S., Poo, M., Zeng, Y., & Xu, B.* ( (2021) Self-backpropagation of synaptic modifications elevates the efficiency of spiking and artificial neural networks. Science Advances 7: eabh0146. |
| • Zhang, T.*, Zeng, Y.*, Zhang, Y., Zhang, X., Shi, M., Tang, L., Zhang, D. & Xu, B. (2021) Neuron type classification in rat brain based on integrative convolutional and tree-based recurrent neural networks. Scientific Reports 11: 7291. |
| • Zhang, T.*, Jia, S., Cheng, X., & Xu, B.* (2021) Tuning Convolutional Spiking Neural Network With Biologically Plausible Reward Propagation. IEEE Transactions on Neural Networks and Learning Systems 33: 7621-7631. |
| • Xing, D., Li, J., Zhang, T.*, & Xu, B. (2021) A Brain-Inspired Approach for Collision-Free Movement Planning in the Small Operational Space. I IEEE Transactions on Neural Networks and Learning Systems 33: 2094-2105. |
| • Zhang, T., & Xu, B.* (2021) 脉冲神经网络研究现状及展望, Research Advances and Perspectives on Spiking Neural Networks. 计算机学报, Chinese Journal of Computers 44: 1767-1785. |
| • Jia, S.#,Zhang, T.#*, Cheng, X., Liu, H., & Xu, B.* (2021) Neuronal-Plasticity and Reward-Propagation Improved Recurrent Spiking Neural Networks. Frontiers in Neuroscience 15: 654786. |
| • Wei, Q.*, Han, L., & Zhang, T. (2021) Spiking Adaptive Dynamic Programming Based on Poisson Process for Discrete-Time Nonlinear Systems. IEEE Transactions on Neural Networks and Learning Systems 33:: 1846-1856. |
| • Wei, Q.*, Han, L., & Zhang, T. (2021) Spiking Adaptive Dynamic Programming with Poisson Process. International Conference on Swarm Intelligence : 525-535. |
| • Sun, Y., Zeng, Y., & Zhang, T. (2021) Quantum Superposition Inspired Spiking Neural Network. IScience : 24. |
| • Zhang, Q., Zeng, Y., Zhang, T., & Yang, T. (2021) Comparison Between Human and Rodent Neurons for Persistent Activity Performance: A Biologically Plausible Computational Investigation. Frontiers in System Neuroscience 15: 628839. |
| • Zhang, T., Zeng, Y., Pan, R., Shi, M., & Lu, E. (2020) Brain-Inspired Active Learning Architecture for Procedural Knowledge Understanding Based on Human-Robot Interaction. Cognitive Computation 13: 381-393. |
| • Zhang, T., Yang, Y., Zeng, Y., & Zhao, Y. (2020) Cognitive Template-clustering Improved LineMod for Efficient Multi-object Pose Estimation. Cognitive Computation 12: 834 - 843. |
| • Zhao, D., Zeng, Y., Zhang, T., Shi, M., & Zhao, F. (2020) GLSNN: A Multi-layer Spiking Neural Network based on Global Feedback Alignment and Local STDP Plasticity. Frontiers in Computational Neuroscience 14: 576841. |
| • Zeng, Y., Zhao, Y., Zhang, T., Zhao, D., Zhao, F., & Lu, E. (2020) A Brain-Inspired Model of Theory of Mind. Frontiers in Neurorobotics 14: 60. |
| • Shi, M.#, Zhang, T.#, & Zeng, Y. (2020) A Curiosity-Based Learning Method for Spiking Neural Networks. Frontiers in Computational Neuroscience 14: 7. |
| • Zuo, G., Pan, T., & Zhang, T. (2019) SOAR Improved Artificial Neural Network for Multistep Decision-Making Tasks. Cognitive Computation 13: 612-625. |
| • Zhang, T., Zeng, Y., Zhao, D., & Shi, M. (2019) A Plasticity-centric Approach to Train the Non-differential Spiking Neural Networks, AAAI Conference on Artificial Intelligence : 32. |
| • Zhang, T., Zeng, Y., Zhao, D., & Xu, B. (2018) Brain-inspired Balanced Tuning for Spiking Neural Networks. The 27th International Joint Conference on Artificial Intelligence 7: 1653-1659. |
| • Mizrahi, D., Laufer, I., Zuckerman, I., & Zhang, T. (2018) The Effect of Culture and Social Orientation on Player'sPerformances in Tacit Coordination Games. International Conference on Brain Informatics : 437-447. |
| • Zhang, T., Zeng, Y., & Xu, B. (2017) A computational approach towards the microscale mouse brain connectome from the mesoscale. Journal of Integrative Neuroscience 16: 291-306. |
| • Zeng, Y.#, Zhang, T.#, & Xu, B. (2017) Improving multi-layer spiking neural networks by incorporating braininspired rules. Science China-Information Sciences 60: 052201. |
| • Zhao, F., Zhang, T. (Co-first), Zeng, Y. & Xu, B. (2017) owards a Brain-Inspired Developmental Neural Network by Adaptive Synaptic Pruning. The 24th international Conference on Neural Information Processing : 182-191. |
| • Liu, X., Zeng, Y., Zhang, T.., & Xu, B. (2016) Parallel Brain Simulator: A Multi-scale and Parallel Brain-inspired Neural Network Modeling and Simulation Platform. Cognitive Computation 8: 967-981. |
| • Zhang, T., Zeng, Y., & Xu, B. (2016) HCNN: A Neural Network Model for Combining Local and Global Features towards Human-like Classification. International Journal of Pattern Recognition and Artificial Intelligence 30: 1655004. |
| • Zhang, T., Zeng, Y., Zhao, D., Wang, L., Zhao, Y., & Xu, B. (2016) HMSNN: Hippocampus inspired Memory Spiking Neural Network. Proceedings of the 2016 IEEE International Conference on Systems, Man, and Cybernetics : 002301-002306. |
| • Zhang, T., Zeng, Y. & Xu, B. (2015) Biological Neural Network Structure and Spike Activity Prediction based on Multi-neuron Spike Train Data. International Journal of Intelligence Science 5: 102. |
| • Zeng, Y., Wang, D., Zhang, T. & Xu, B. (2014) Linked Neuron Data (LND): A Platform for Integrating and Semantically Linking Neuroscience Data and Knowledge. Frontiers in Neuroinformatics. Conference Abstract: The 7th Neuroinformatics Congress : : 17. |
| • Zeng, Y., Zhang, T.., & Hao, H. (2014) Active Recommendation of Tourist Attractions based on Visitors Interests and Semantic Relatedness. Proceedings of the 2014 International Conference on Active Media Technology : |
| • Zeng, Y.#, Zhang, T.#, & Xu, B. (2014) Neural Pathway Prediction based on Multi-neuron Spike Train Data. The Twenty-Third Annual Computational Neuroscience Meeting 15: P6. |
| • Zhang, T., Zeng, Y., & Xu, B. (2014) Neural Spike Prediction based on Spreading Activation. The Twenty-Third Annual Computational Neuroscience Meeting 15: P7. |
| • Zeng, Y., Wang, D., Zhang, T.., Wang, H., Hao, H., & Xu, B. (2013) CASIA-KB: A Multi-source Chinese Semantic Knowledge Base Built from Structured and Unstructured Web Data. Proceedings of the 3rd Joint International Semantic Technology Conference : 75-88. |
| • Zeng, Y., Wang, D., Zhang, T., Wang, H., & Hao, H. (2013) Linking Entities in Short Texts based on a Chinese Semantic Knowledge Base. Proceedings of the 2nd Conference on Natural Language Processing and Chinese Computing : 266-276. |
