Interpretable Polynomial Neural Ordinary Differential Equations
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DOI: 10.1063/5.0130803
Abstract: Neural networks have the ability to serve as universal function approximators, but they are not interpretable and do not generalize well outside of their training region. Both of these issues are problematic when trying to… read more here.
Keywords: ordinary differential; interpretable polynomial; polynomial neural; neural ordinary ... See more keywords
Crop Classification Under Varying Cloud Cover With Neural Ordinary Differential Equations
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2021.3101965
Abstract: Optical satellite sensors cannot see the earth’s surface through clouds. Despite the periodic revisit cycle, image sequences acquired by earth observation satellites are, therefore, irregularly sampled in time. State-of-the-art methods for crop classification (and other… read more here.
Keywords: neural ordinary; crop; classification; crop classification ... See more keywords
Optical Neural Ordinary Differential Equations
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DOI: 10.1364/ol.477713
Abstract: Increasing the layer number of on-chip photonic neural networks (PNNs) is essential to improve its model performance. However, the successive cascading of network hidden layers results in larger integrated photonic chip areas. To address this… read more here.
Keywords: neural networks; optical neural; hidden layer; ordinary differential ... See more keywords