eLife

Designing optimal perturbation inputs for system identification in neuroscience

To enable more accurate estimation of connectivity, we propose a data-driven and theoretically grounded framework for optimally designing perturbation inputs, based on formulating the neural model as ...
IEEE

Multidimensional Image Reconstruction via Deep Nonlinear Low-Rank Tensor Decomposition

Abstract: Low-rank tensor decomposition (LRTD) has demonstrated significant efficacy in multidimensional image reconstruction. Indeed, LRTD driven by nonlinear relationship can capture the underlying ...
C&EN

Development and Application of a Multidimensional Database for the Detection of Quaternary Ammonium Compounds and Their Phase I Hepatic Metabolites in Humans

Department of Medicinal Chemistry, University of Washington, Seattle, Washington 98195, United States ...
GitHub

Array parameters not pulling through into example snippet in some languages in API Client

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IEEE

Deep Fractional Multidimensional Spectrum Convolutional Neural Fusion Network for Identifying Complex Power Quality Disturbance

The widespread utilization of renewable energy sources can cause serious power quality problems. It presents new challenges for detecting power quality. A deep fractional multidimensional spectrum ...