9 citations · 34 across the 15 of their papers we have counts for
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cs.NE2023★ 4 cited
Artificial to Spiking Neural Networks Conversion for Scientific Machine Learning
Qian Zhang, Chenxi Wu, Adar Kahana +4
We introduce a method to convert Physics-Informed Neural Networks (PINNs), commonly used in scientific machine learning, to Spiking Neural Networks (SNNs), which are expected to ha…
cs.NE2022
Spiking Neural Operators for Scientific Machine Learning
Adar Kahana, Qian Zhang, Leonard Gleyzer +1
The main computational task of Scientific Machine Learning (SciML) is function regression, required both for inputs as well as outputs of a simulation. Physics-Informed Neural Netw…