Masquelier, Timothée

9 publications

NeurIPS 2025 Multiplication-Free Parallelizable Spiking Neurons with Efficient Spatio-Temporal Dynamics Peng Xue, Wei Fang, Zhengyu Ma, Zihan Huang, Zhaokun Zhou, Yonghong Tian, Timothée Masquelier, Huihui Zhou

ICLR 2024 Learning Delays in Spiking Neural Networks Using Dilated Convolutions with Learnable Spacings Ilyass Hammouamri, Ismail Khalfaoui-Hassani, Timothée Masquelier

ICLR 2023 Dilated Convolution with Learnable Spacings Ismail Khalfaoui Hassani, Thomas Pellegrini, Timothée Masquelier

ICMLW 2023 Dilated Convolution with Learnable Spacings: Beyond Bilinear Interpolation Ismail Khalfaoui-Hassani, Thomas Pellegrini, Timothée Masquelier

NeurIPS 2023 Parallel Spiking Neurons with High Efficiency and Ability to Learn Long-Term Dependencies Wei Fang, Zhaofei Yu, Zhaokun Zhou, Ding Chen, Yanqi Chen, Zhengyu Ma, Timothée Masquelier, Yonghong Tian

TMLR 2022 Mitigating Catastrophic Forgetting in Spiking Neural Networks Through Threshold Modulation Ilyass Hammouamri, Timothée Masquelier, Dennis George Wilson

NeurIPS 2022 Training Spiking Neural Networks with Event-Driven Backpropagation Yaoyu Zhu, Zhaofei Yu, Wei Fang, Xiaodong Xie, Tiejun Huang, Timothée Masquelier

NeurIPS 2021 Deep Residual Learning in Spiking Neural Networks Wei Fang, Zhaofei Yu, Yanqi Chen, Tiejun Huang, Timothée Masquelier, Yonghong Tian

ICCV 2021 Incorporating Learnable Membrane Time Constant to Enhance Learning of Spiking Neural Networks Wei Fang, Zhaofei Yu, Yanqi Chen, Timothée Masquelier, Tiejun Huang, Yonghong Tian