TDAPNet: Prototype Network with Recurrent Top-Down Attention for Robust Object Classification under Partial Occlusion. - Mingqing Xiao 002; Adam Kortylewski; Ruihai Wu; Siyuan Qiao; Wei Shen 002; Alan L. Yuille (CoRR, 2019)

TDMPNet: Prototype Network with Recurrent Top-Down Modulation for Robust Object Classification Under Partial Occlusion. - Mingqing Xiao 002; Adam Kortylewski; Ruihai Wu; Siyuan Qiao; Wei Shen 002; Alan L. Yuille (ECCV Workshops (2), 2020)

Invertible Image Rescaling. - Mingqing Xiao 002; Shuxin Zheng; Chang Liu 030; Yaolong Wang; Di He 001; Guolin Ke; Jiang Bian 002; Zhouchen Lin; Tie-Yan Liu (ECCV (1), 2020)

Modeling Lost Information in Lossy Image Compression. - Yaolong Wang; Mingqing Xiao 002; Chang Liu 030; Shuxin Zheng; Tie-Yan Liu (CoRR, 2020)

Training Feedback Spiking Neural Networks by Implicit Differentiation on the Equilibrium State. - Mingqing Xiao 002; Qingyan Meng; Zongpeng Zhang; Yisen Wang 001; Zhouchen Lin (NeurIPS, 2021)

Training High-Performance Low-Latency Spiking Neural Networks by Differentiation on Spike Representation. - Qingyan Meng; Mingqing Xiao 002; Shen Yan 004; Yisen Wang 001; Zhouchen Lin; Zhi-Quan Luo (CVPR, 2022)

Online Training Through Time for Spiking Neural Networks. - Mingqing Xiao 002; Qingyan Meng; Zongpeng Zhang; Di He 001; Zhouchen Lin (NeurIPS, 2022)

Training much deeper spiking neural networks with a small number of time-steps. - Qingyan Meng; Shen Yan 004; Mingqing Xiao 002; Yisen Wang 001; Zhouchen Lin; Zhi-Quan Luo (Neural Networks, 2022)

Training Neural Networks by Lifted Proximal Operator Machines. - Jia Li 002; Mingqing Xiao 002; Cong Fang 001; Yue Dai 003; Chao Xu 006; Zhouchen Lin (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

Towards Memory- and Time-Efficient Backpropagation for Training Spiking Neural Networks. - Qingyan Meng; Mingqing Xiao 002; Shen Yan 004; Yisen Wang 001; Zhouchen Lin; Zhi-Quan Luo (ICCV, 2023)

Invertible Rescaling Network and Its Extensions. - Mingqing Xiao 002; Shuxin Zheng; Chang Liu 030; Zhouchen Lin; Tie-Yan Liu (Int. J. Comput. Vis., 2023)

SPIDE: A purely spike-based method for training feedback spiking neural networks. - Mingqing Xiao 002; Qingyan Meng; Zongpeng Zhang; Yisen Wang 001; Zhouchen Lin (Neural Networks, 2023)

Hebbian Learning based Orthogonal Projection for Continual Learning of Spiking Neural Networks. - Mingqing Xiao 002; Qingyan Meng; Zongpeng Zhang; Di He 001; Zhouchen Lin (ICLR, 2024)

Temporal Spiking Neural Networks with Synaptic Delay for Graph Reasoning. - Mingqing Xiao 002; Yixin Zhu; Di He 001; Zhouchen Lin (ICML, 2024)

Cross-patient automatic epileptic seizure detection using patient-adversarial neural networks with spatio-temporal EEG augmentation. - Zongpeng Zhang; Taoyun Ji; Mingqing Xiao 002; Wen Wang; Guojing Yu; Tong Lin 002; Yuwu Jiang; Xiaohua Zhou; Zhouchen Lin (Biomed. Signal Process. Control., 2024)

Online Pseudo-Zeroth-Order Training of Neuromorphic Spiking Neural Networks. - Mingqing Xiao 002; Qingyan Meng; Zongpeng Zhang; Di He 001; Zhouchen Lin (CoRR, 2024)

Sampling complex topology structures for spiking neural networks. - Shen Yan 004; Qingyan Meng; Mingqing Xiao 002; Yisen Wang 001; Zhouchen Lin (Neural Networks, 2024)

Designing Universally-Approximating Deep Neural Networks: A First-Order Optimization Approach. - Zhoutong Wu; Mingqing Xiao 002; Cong Fang 001; Zhouchen Lin (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

A Self-Ensemble Inspired Approach for Effective Training of Binary-Weight Spiking Neural Networks. - Qingyan Meng; Mingqing Xiao 002; Zhengyu Ma; Huihui Zhou; Yonghong Tian 001; Zhouchen Lin (CoRR, 2025)