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Showing 1 to 3 of 3 for “"neural ordinary differential equation"”.
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Neural ordinary differential equation models for circuits
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2022-11-15 without embargo terms
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Neural Closure Models for Chaotic Dynamical Systems
… work, we develop a training framework to apply neural ordinary differential equation-based (nODE) closure models to correct errors in the equations of such dynamical systems. We first identify the key training parameters that have an outsize effect on the learning ability of the neural closure …
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Toward Robust and Generalizable Spatiotemporal Modeling for Tasks beyond Forecasting and Classification
… spatial and temporal dependencies intrinsic to neural activity. In response, we propose a novel spatiotemporal deep learning model tailored for depression-related EEG analysis. The architecture integrates multiple trainable denoising modules within an end-to-end pipeline, reducing the need for …