The application of spatial Lorenz curve (SLC) and Gini coefficient in measuring land use structure change. - Yu Song; Quanyi Qiu; Qinghai Guo; Jianyi Lin; Fangyi Li; Yuxian Yu; Xuanqi Li; Lina Tang (Geoinformatics, 2010)

SoftHebb: Bayesian inference in unsupervised Hebbian soft winner-take-all networks. - Timoleon Moraitis; Dmitry Toichkin; Yansong Chua; Qinghai Guo (CoRR, 2021)

Replay-Oriented Gradient Projection Memory for Continual Learning in Medical Scenarios. - Kuang Shu; Heng Li 010; Jie Cheng; Qinghai Guo; Luziwei Leng; Jianxing Liao; Yan Hu; Jiang Liu 001 (BIBM, 2022)

Discrete time convolution for fast event-based stereo. - Kaixuan Zhang; Kaiwei Che; Jianguo Zhang; Jie Cheng; Ziyang Zhang; Qinghai Guo; Luziwei Leng (CVPR, 2022)

Spike-inspired rank coding for fast and accurate recurrent neural networks. - Alan Jeffares; Qinghai Guo; Pontus Stenetorp; Timoleon Moraitis (ICLR, 2022)

Variational Predictive Routing with Nested Subjective Timescales. - Alexey Zakharov; Qinghai Guo; Zafeirios Fountas (ICLR, 2022)

Short-Term Plasticity Neurons Learning to Learn and Forget. - Hector Garcia Rodriguez; Qinghai Guo; Timoleon Moraitis (ICML, 2022)

Attentive Decision-making and Dynamic Resetting of Continual Running SRNNs for End-to-End Streaming Keyword Spotting. - Bojian Yin; Qinghai Guo; Federico Corradi; Sander M. Bohté (ICONS, 2022)

Differentiable hierarchical and surrogate gradient search for spiking neural networks. - Kaiwei Che; Luziwei Leng; Kaixuan Zhang; Jianguo Zhang; Qinghu Meng; Jie Cheng; Qinghai Guo; Jianxing Liao (NeurIPS, 2022)

Self-Supervised Learning Through Efference Copies. - Franz Scherr; Qinghai Guo; Timoleon Moraitis (NeurIPS, 2022)

DevFly: Bio-Inspired Development of Binary Connections for Locality Preserving Sparse Codes. - Tianqi Wei 001; Rana Alkhoury Maroun; Qinghai Guo; Barbara Webb (NeurIPS, 2022)

Modelling non-reinforced preferences using selective attention. - Noor Sajid; Panagiotis Tigas; Zafeirios Fountas; Qinghai Guo; Alexey Zakharov; Lancelot Da Costa (CoRR, 2022)

Long-horizon video prediction using a dynamic latent hierarchy. - Alexey Zakharov; Qinghai Guo; Zafeirios Fountas (CoRR, 2022)

SoftHebb: Bayesian inference in unsupervised Hebbian soft winner-take-all networks. - Timoleon Moraitis; Dmitry Toichkin; Adrien Journé; Yansong Chua; Qinghai Guo (Neuromorph. Comput. Eng., 2022)

Neuro-Modulated Hebbian Learning for Fully Test-Time Adaptation. - Yushun Tang; Ce Zhang 009; Heng Xu; Shuoshuo Chen; Jie Cheng; Luziwei Leng; Qinghai Guo; Zhihai He (CVPR, 2023)

Weakly-Supervised Action Localization by Hierarchically-structured Latent Attention Modeling. - Guiqin Wang; Peng Zhao 001; Cong Zhao 001; Shusen Yang; Jie Cheng; Luziwei Leng; Jianxing Liao; Qinghai Guo (ICCV, 2023)

Cross-Inferential Networks for Source-Free Unsupervised Domain Adaptation. - Yushun Tang; Qinghai Guo; Zhihai He (ICIP, 2023)

Hebbian Deep Learning Without Feedback. - Adrien Journé; Hector Garcia Rodriguez; Qinghai Guo; Timoleon Moraitis (ICLR, 2023)

Learning Task-Specific Morphological Representation for Pyramidal Cells via Mutual Information Minimization. - Chunli Sun; Qinghai Guo; Gang Yang; Feng Zhao 004 (PRIME@MICCAI, 2023)

Learning and processing the ordinal information of temporal sequences in recurrent neural circuits. - Xiaolong Zou; Zhikun Chu; Qinghai Guo; Jie Cheng; Bo Ho; Si Wu 001; Yuanyuan Mi (NeurIPS, 2023)

Curvature-Sensitive Predictive Coding with Approximate Laplace Monte Carlo. - Umais Zahid; Qinghai Guo; Karl J. Friston; Zafeirios Fountas (CoRR, 2023)

Accurate and Efficient Event-based Semantic Segmentation Using Adaptive Spiking Encoder-Decoder Network. - Rui Zhang; Luziwei Leng; Kaiwei Che; Hu Zhang; Jie Cheng; Qinghai Guo; Jiangxing Liao; Ran Cheng (CoRR, 2023)

Automotive Object Detection via Learning Sparse Events by Temporal Dynamics of Spiking Neurons. - Hu Zhang; Luziwei Leng; Kaiwei Che; Qian Liu; Jie Cheng; Qinghai Guo; Jiangxing Liao; Ran Cheng (CoRR, 2023)

Predictive Coding as a Neuromorphic Alternative to Backpropagation: A Critical Evaluation. - Umais Zahid; Qinghai Guo; Zafeirios Fountas (Neural Comput., 2023)

Fusion Side Tuning: A Parameter and Memory Efficient Fine-tuning Method for High-resolution Medical Image Classification. - Zhangchi Wang; Yijin Huang; Yidu Wu; Pujin Cheng; Li Lin 006; Qinghai Guo; Xiaoying Tang 001 (BIBM, 2024)

BKDSNN: Enhancing the Performance of Learning-Based Spiking Neural Networks Training with Blurred Knowledge Distillation. - Zekai Xu; Kang You; Qinghai Guo; Xiang Wang; Zhezhi He (ECCV (50), 2024)

SpikeZIP-TF: Conversion is All You Need for Transformer-based SNN. - Kang You; Zekai Xu; Chen Nie; Zhijie Deng; Qinghai Guo; Xiang Wang; Zhezhi He (ICML, 2024)

Sample as you Infer: Predictive Coding with Langevin Dynamics. - Umais Zahid; Qinghai Guo; Zafeirios Fountas (ICML, 2024)

SpikingMiniLM: energy-efficient spiking transformer for natural language understanding. - Jiayu Zhang; Jiangrong Shen; Zeke Wang; Qinghai Guo; Rui Yan 005; Gang Pan 001; Huajin Tang (Sci. China Inf. Sci., 2024)

When in Doubt, Think Slow: Iterative Reasoning with Latent Imagination. - Martin Benfeghoul; Umais Zahid; Qinghai Guo; Zafeirios Fountas (CoRR, 2024)

Benchmarking Neural Decoding Backbones towards Enhanced On-edge iBCI Applications. - Zhou Zhou; Guohang He; Zheng Zhang; Luziwei Leng; Qinghai Guo; Jianxing Liao; Xuan Song; Ran Cheng (CoRR, 2024)

Learning Visual Conditioning Tokens to Correct Domain Shift for Fully Test-time Adaptation. - Yushun Tang; Shuoshuo Chen; Zhehan Kan; Yi Zhang 109; Qinghai Guo; Zhihai He (CoRR, 2024)

SPikE-SSM: A Sparse, Precise, and Efficient Spiking State Space Model for Long Sequences Learning. - Yan Zhong; Ruoyu Zhao; Chao Wang; Qinghai Guo; Jianguo Zhang; Zhichao Lu; Luziwei Leng (CoRR, 2024)

Learning with sparse reward in a gap junction network inspired by the insect mushroom body. - Tianqi Wei 001; Qinghai Guo; Barbara Webb (PLoS Comput. Biol., 2024)

Evolutionary spiking neural networks: a survey. - Shuaijie Shen; Rui Zhang 042; Chao Wang; Renzhuo Huang; Aiersi Tuerhong; Qinghai Guo; Zhichao Lu; Jianguo Zhang; Luziwei Leng (J. Membr. Comput., 2024)

Automotive Object Detection via Learning Sparse Events by Spiking Neurons. - Hu Zhang; Yanchen Li; Luziwei Leng; Kaiwei Che; Qian Liu; Qinghai Guo; Jianxing Liao; Ran Cheng (IEEE Trans. Cogn. Dev. Syst., 2024)

SpikingSSMs: Learning Long Sequences with Sparse and Parallel Spiking State Space Models. - Shuaijie Shen; Chao Wang; Renzhuo Huang; Yan Zhong; Qinghai Guo; Zhichao Lu; Jianguo Zhang; Luziwei Leng (AAAI, 2025)

VISTREAM: Improving Computation Efficiency of Visual Streaming Perception via Law-of-Charge-Conservation Inspired Spiking Neural Network. - Kang You; Ziling Wei; Jing Yan; Boning Zhang; Qinghai Guo; Yaoyu Zhang; Zhezhi He (CVPR, 2025)

Explicit Mutual Information Maximization for Self-Supervised Learning. - Lele Chang; Peilin Liu; Qinghai Guo; Fei Wen (ICASSP, 2025)

Threshold Modulation for Online Test-Time Adaptation of Spiking Neural Networks. - Kejie Zhao; Wenjia Hua; Aiersi Tuerhong; Luziwei Leng; Yuxin Ma; Qinghai Guo (CoRR, 2025)

Accurate and Efficient Event-Based Semantic Segmentation Using Adaptive Spiking Encoder-Decoder Network. - Rui Zhang; Luziwei Leng; Kaiwei Che; Hu Zhang; Jie Cheng; Qinghai Guo; Jianxing Liao; Ran Cheng (IEEE Trans. Neural Networks Learn. Syst., 2025)