3 citations · 3 across the 2 of their papers we have counts for
2 papers
stat.ML2023★ 3 cited
Universal Scaling Laws of Absorbing Phase Transitions in Artificial Deep Neural Networks
Keiichi Tamai, Tsuyoshi Okubo, Truong Vinh Truong Duy +2
We demonstrate that conventional artificial deep neural networks operating near the phase boundary of the signal propagation dynamics, also known as the edge of chaos, exhibit univ…
cs.NE2022
Rethinking the role of normalization and residual blocks for spiking neural networks
Shin-ichi Ikegawa, Ryuji Saiin, Yoshihide Sawada +1
Biologically inspired spiking neural networks (SNNs) are widely used to realize ultralow-power energy consumption. However, deep SNNs are not easy to train due to the excessive fir…