Adversarially Robust Spiking Neural Networks Through Conversion

15 November 2023

Papers citing "Adversarially Robust Spiking Neural Networks Through Conversion"

8 / 8 papers shown

Title
HoSNN: Adversarially-Robust Homeostatic Spiking Neural Networks with Adaptive Firing Thresholds Hejia Geng Peng Li AAML 30 3 0 20 Aug 2023
Optimal ANN-SNN Conversion for High-accuracy and Ultra-low-latency Spiking Neural Networks Tong Bu Wei Fang Jianhao Ding Penglin Dai Zhaofei Yu Tiejun Huang 105 195 0 08 Mar 2023
Temporal Efficient Training of Spiking Neural Network via Gradient Re-weighting Shi-Wee Deng Yuhang Li Shanghang Zhang Shi Gu 112 243 0 24 Feb 2022
Deep Residual Learning in Spiking Neural Networks Wei Fang Zhaofei Yu Yanqing Chen Tiejun Huang T. Masquelier Yonghong Tian 121 475 0 08 Feb 2021
RobustBench: a standardized adversarial robustness benchmark Francesco Croce Maksym Andriushchenko Vikash Sehwag Edoardo Debenedetti Nicolas Flammarion M. Chiang Prateek Mittal Matthias Hein VLM 217 675 0 19 Oct 2020
Enabling Deep Spiking Neural Networks with Hybrid Conversion and Spike Timing Dependent Backpropagation Nitin Rathi G. Srinivasan Priyadarshini Panda Kaushik Roy 119 293 0 04 May 2020
Inherent Adversarial Robustness of Deep Spiking Neural Networks: Effects of Discrete Input Encoding and Non-Linear Activations Saima Sharmin Nitin Rathi Priyadarshini Panda Kaushik Roy AAML 106 85 0 23 Mar 2020
Long short-term memory and learning-to-learn in networks of spiking neurons G. Bellec Darjan Salaj Anand Subramoney R. Legenstein Wolfgang Maass 111 481 0 26 Mar 2018