3 papers
cs.NE2025
From LIF to QIF: Toward Differentiable Spiking Neurons for Scientific Machine Learning
Ruyin Wan, George Em Karniadakis, Panos Stinis
Spiking neural networks (SNNs) offer biologically inspired computation but remain underexplored for continuous regression tasks in scientific machine learning. In this work, we int…
cs.LG2025
DeepVIVONet: Using deep neural operators to optimize sensor locations with application to vortex-induced vibrations
Ruyin Wan, Ehsan Kharazmi, Michael S Triantafyllou +1
We introduce DeepVIVONet, a new framework for optimal dynamic reconstruction and forecasting of the vortex-induced vibrations (VIV) of a marine riser, using field data. We demonstr…
cs.NE2024
Randomized Forward Mode Gradient for Spiking Neural Networks in Scientific Machine Learning
Ruyin Wan, Qian Zhang, George Em Karniadakis
Spiking neural networks (SNNs) represent a promising approach in machine learning, combining the hierarchical learning capabilities of deep neural networks with the energy efficien…