continuous-time dynamics 1differentiable training 1memory efficiency 1neuromorphic computing 1spiking neural networks 1
From the 1 of 2 linked papers with an AI index.
2 papers
cs.LG2026
Scalable Training of Continuous-Time Spiking Neural Networks with Differentiable Spike-Time Discretization
Yusuke Sakemi, Tomoya Takeuchi, Takeo Hosomi +1
The paper proposes a memory‑efficient training method for continuous‑time spiking neural networks by discretizing spike times into differentiable weighted events, enabling deep SNN…
stat.ML2025
Learning the Simplest Neural ODE
Yuji Okamoto, Tomoya Takeuchi, Yusuke Sakemi
Since the advent of the ``Neural Ordinary Differential Equation (Neural ODE)'' paper, learning ODEs with deep learning has been applied to system identification, time-series foreca…