S2NN: Time Step Reduction of Spiking Surrogate Gradients for Training Energy Efficient Single-Step Neural Networks. - Kazuma Suetake; Shin-ichi Ikegawa; Ryuji Saiin; Yoshihide Sawada (CoRR, 2022)

Rethinking the Role of Normalization and Residual Blocks for Spiking Neural Networks. - Shin-ichi Ikegawa; Ryuji Saiin; Yoshihide Sawada; Naotake Natori (Sensors, 2022)

S3NN: Time step reduction of spiking surrogate gradients for training energy efficient single-step spiking neural networks. - Kazuma Suetake; Shin-ichi Ikegawa; Ryuji Saiin; Yoshihide Sawada (Neural Networks, 2023)