Publications

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[Research Gate]

Publications with Supplementary Materials: 

1. Zhang, S., Liu, J. K., SeqProFT: Sequence-only Protein Property Prediction with LoRA Finetuning, IEEE Transactions on Artificial Intelligence 7(6) 3194-3204 (2026)  [PDF][CODE] DOI: 10.1109/TAI.2025.3636109

2. Zhang, S., Hong, R., Zhang, H., Liu, J. K., Hierarchical Contrastive Learning for Multi-Domain Protein-Ligand Binding, 22nd International Symposium on Bioinformatics Research and Applications (2026)  [PDF][CODE] DOI: 10.48550/arXiv.2605.19902

3. Li, Y., Wang, S., Liu, J. K. Copilot-Assisted Second-Thought Framework for Brain-to-Robot Hand Motion Decoding, 2026 Joint International Conference on Automation-Intelligence-Safety (ICAIS) & International Symposium on Autonomous Systems (ISAS) (2026)  [PDF][CODE] DOI: 10.48550/arXiv.2603.27492

4. Zhang, S., Liu, J. K., Domain-Aware Geometric Multimodal Learning for Multi-Domain Protein-Ligand Affinity Prediction, 14th International Conference on Bioinformatics and Computational Biology (2026)  [PDF][CODE] DOI: 10.48550/arXiv.2601.17102

5. Fang, Z., Wan, B., Guo, S., Liu, J. K., HMEN: A Hybrid Modular Network with Dynamic Expansion for Continual Learning, Knowledge-Based Systems  335, 115182 (2026) [PDF][CODE] DOI: 10.1016/j.knosys.2025.115182

6. Bouwen, B., Bolleboom, A., Tang, Y., Yu, Z., van der Stap, A., van Rij, J., van Dis, V., Dirven, C., de Zeeuw, C., van Tellingen, O., Liu, J. K., Vincent, A., Gao, Z., Aberrant neural activity in the peritumoral cortex underlies the progression of tumor associated seizures, Nature Communications, 16, 10846 (2025). [PDF][[CODE]  DOI:10.1038/s41467-025-66226-5

7. Ding, J., Yu, Z., Liu, J. K., Huang, T., Neuromorphic computing paradigms enhance robustness through spiking neural networks, Nature Communications, 16, 10175 (2025). [PDF][CODE]  DOI:10.1038/s41467-025-65197-x

8. Peng, J., Jia, S, Zhang, J., Wang, Y., Yu, Z., Liu, J. K., Decoding Natural Visual Scenes via Learnable Representations of Neural Spiking Sequences, Neural Netw.  192, 107863 (2025)  [PDF] [CODE] DOI: 10.1016/j.neunet.2025.107863

9. Huang, Z., Ding, J., Pan, Z., Li, H., Fang, Y., Yu, Z., Liu, J. K., Converting High-Performance and Low-Latency SNNs through Explicit Modelling of Residual Error in ANNs, IEEE Transactions on Neural Networks and Learning Systems. 36(9) 16788-16802 (2025) [PDF]  [Code] DOI: 10.1109/TNNLS.2025.3567567

10. Tang, Y., Jia, S, Huang, T., Yu, Z., Liu, J. K., Implementing feature binding through dendritic networks of a single neuron, Neural Netw. 189, 107555 (2025)  [PDF] [CODE] DOI: 10.1016/j.neunet.2025.107555

11. Yang, Z., Guo, S., Fang, Y., Yu, Z., Liu, J. K., Spiking Variational Policy Gradient for Brain Inspired Reinforcement Learning, IEEE Transactions on Pattern Analysis and Machine Intelligence. 47(3) 1975-1990 (2025) [PDF] [Code] DOI: 10.1109/TPAMI.2024.3511936

12. Zhou, F., Zhang, S., Zhang, H., Liu, J. K., ProCeSa: Contrast-Enhanced Structure-Aware Network for Thermostability Prediction with Protein Language Models, J. Chem. Inf. Model. 65(5), 2304–2313 (2025) [PDF] [Code] DOI: 10.1021/acs.jcim.4c01752

13. Wu, R., Zhou, F., Yin, Z., Liu, J. K., Aligning Neuronal Coding of Dynamic Visual Scenes with Foundation Vision Models, European Conference on Computer Vision (ECCV). (2024) [PDF] [Poster/Video] [CODE] DOI: 10.1007/978-3-031-73223-2_14

14. Yang, R., Zhao, P., Wang, L., Feng, C., Peng, C., Wang, Z., Zhang, Y., Shen, M., Shi, K., Weng, S., Dong, C., Zeng, F., Zhang, T., Chen, X., Wang, S., Wang, Y., Luo, Y., Chen, Q., Shi, G., Zhu, Y., Liu, J. K., Li, X., HeGCL: Advance Self-Supervised Learning in Heterogeneous Graph-Level Representation. IEEE Transactions on Neural Networks and Learning Systems. 35(10) 13914-13925 (2024) [PDF] [CODE] DOI: 10.1109/TNNLS.2023.3273255

15. Chen, Y., Beech, P., Yin, Z., Jia, S., Zhang, J., Yu, Z., Liu, J. K., Decoding dynamic visual scenes across the brain hierarchy, PLoS Comput Biol 20(8): e1012297 (2024) [PDF]  [Code] DOI: 10.1371/journal.pcbi.1012297

16. Chen, Y., Feng, R., Xiong, Z., Xiao, J., Liu, J. K., High-performance deep spiking neural networks via at-most-two-spike exponential coding, Neural Netw 176, 106346 (2024) [PDF] [Code] DOI: 10.1016/j.neunet.2024.106346

17. Chen, L., Wu, R., Zhou, F., Zhang, H., Liu, J. K., HybridGCN for Protein Solubility Prediction with Adaptive Weighting of Multiple Features. Journal of Cheminformatics  15, 118 (2023) [PDF] [CODE] DOI: 10.1186/s13321-023-00788-8

18. Tang Y., Zhang X., An L., Yu Z., Liu, J. K., Diverse role of NMDA receptors for dendritic integration of neural dynamics, PLoS Comput Biol (2023) 19(4): e1011019 (2023) [PDF]  [Code] DOI: 10.1371/journal.pcbi.1011019

19. Ding, J., Bu, T., Yu, Z., Huang, T., Liu, J.K., SNN-RAT: Robustness-enhanced Spiking Neural Network through Regularized Adversarial Training, Advances in Neural Information Processing Systems (NeurIPS) (2022) [Spotlight] [PDF] [Poster] [Code] [Metapage]

20. Yang, Z., Guo, S., Fang, Y., Liu, J.K. Biologically Plausible Variational Policy Gradient with Spiking Recurrent Winner-Take-All Networks, British Machine Vision Conference (BMVC) (2022)  [PDF] [Poster]  [Video]  [Code] [Metapage] DOI: 10.48550/arXiv.2210.13225

21. Jia S, Yu Z, Onken A, Tian Y, Huang T, Liu J. K. Neural System Identification with Spike-triggered Non-negative Matrix Factorization. IEEE Transactions on Cybernetics 52(6): 4772-4783 (2022) [PDF] [Code for STNMF] [Code for Copula] [Data] DOI: 10.1109/TCYB.2020.3042513

22. Liu, J. K., Karamanlis, D., Gollisch, T., Simple model for encoding natural images by retinal ganglion cells with nonlinear spatial integration. PLoS Comput Biol 18(3): e1009925 (2022) [PDF] [Data] DOI: 10.1371/journal.pcbi.1009925

23. Yan Q, Zheng Y, Jia S, Zhang Y, Yu Z, Chen F, Tian Y, Huang T, Liu J.K., Revealing Fine Structures of the Retinal Receptive Field by Deep Learning Networks. IEEE Transactions on Cybernetics 52(1) :39-50 (2022) [PDF]  [Code] [Data] DOI: 10.1109/TCYB.2020.2972983 

24. Jia, S., Li, X., Huang, T., Liu, J. K., Zhao, Y., Representing the dynamics of high-dimensional data with non-redundant wavelets. Patterns. 3(3): 100424 (2022)  [PDF] [Code] DOI: 10.1016/j.patter.2021.100424

25. Jia S., Xing D., Yu Z., Liu, J. K., Dissecting cascade computational components in spiking neural networks, PLoS Comput Biol 17(11): e1009640 (2021) [PDF] [Code] DOI: 10.1371/journal.pcbi.1009640

26. Zheng Y, Jia S, Yu Z, Liu, J.K, Huang T. Unraveling neural coding of dynamic natural visual scenes via convolutional recurrent neural networks, Patterns 2(10): 100350 (2021) [PDF] [Code] DOI: 10.1016/j.patter.2021.100350

27. Tang Y., An L., Wang Q., Liu, J. K., Regulating synchronous oscillations of cerebellar granule cells by different types of inhibition, PLoS Comput Biol 17(6): e1009163 (2021) [PDF] [Code] DOI: 10.1371/journal.pcbi.1009163

28. Tang Y., An L., Yuan Y., Pei Q, Wang Q., Liu, J. K., Modulation of the dynamics of cerebellar Purkinje cells through the interaction of excitatory and inhibitory feedforward pathways, PLoS Comput Biol 17(2): e1008670 (2021) [PDF] [Code] DOI: 10.1371/journal.pcbi.1008670

29. Zhang Y, Jia S, Zheng Y, Yu Z, Tian Y., Ma S., Huang T, Liu J.K. Reconstruction of Natural Visual Scenes from Neural Spikes with Deep Neural Networks. Neural Networks. 125:19-30 (2020) [PDF] [Demos] [Code] [Data] DOI: 10.1016/j.neunet.2020.01.033 

30. Liu, J. K., Schreyer, H.M., Onken, A., Rozenblit, F., Khani, M.H., Krishnamoorthy, V.,  Panzeri, S., and Gollisch, T. Inference of neuronal functional circuitry with spike-triggered non-negative matrix factorization, Nature Communications, 8(1):149 (2017). [PDF] [Code] [Data]  [Striking Image]  [Press release in German] [Selected as Gö-VIP (Göttingen Very Important Publication)] DOI:10.1038/s41467-017-00156-9

31. Onken A., Liu J. K., Karunasekara C. R., Delis I., Gollisch T. and Panzeri S. Using Matrix and Tensor Factorizations for the Single-Trial Analysis of Population Spike Trains. PLoS Comput Biol 12(11): e1005189 (2016)  [PDF] [Code] [Data] DOI: 10.1371/journal.pcbi.1005189

32. Zampini, V.*, Liu, J. K.*, Diana, M.A., Maldonado, P.P., Brunel, N., Dieudonné, S. (*These authors contributed equally to this work), Mechanisms and functional roles of glutamatergic synapse diversity in a cerebellar circuit. eLife, 5:e15872 (2016)  [PDF] [Code] DOI: 10.7554/eLife.15872

33. Liu, J. K., Gollisch, T., Spike-Triggered Covariance Analysis Reveals Phenomenological Diversity of Contrast Adaptation in the Retina, PLoS Comput Biol 11(7): e1004425 (2015). [PDF] [Data] (DOI: 10.1371/journal.pcbi.1004425)

34. Liu, J. K., Buonomano, D. V., Embedding Multiple Trajectories in Simulated Recurrent Neural Networks in a Self-Organizing Manner, J. Neuroscience, 29(42):13172-13181. (2009) [PDF] [Suppl. Movie] DOI: 10.1523/JNEUROSCI.2358-09.2009