[2] Structured Matrix Scaling for Multi-Class Calibration (see also: experiments) [3] A Variational Estimator for Lp Calibration Errors (see also all experiments) [4] CalArena: A Large-Scale Post-Hoc ...
Microsoft introduces GridSFM, a small foundation model for solving AC optimal power flow (AC-OPF) problems in transmission power grids. This follows our earlier release of a U.S.-based open ...
This paper proposes Spiking Brain Compression (SBC), a second-order post-training one-shot compression framework based on the Van Rossum Distance, designed specifically for spiking neural networks ...
Timely recognition of oral anticoagulant use is critical in acute stroke but is often hampered by impaired consciousness and unavailable medication history. We investigated whether routinely available ...
This study aimed to identify independent risk factors for DKD in T2DM patients and develop a risk prediction model with internal validation. We retrospectively collected data from 1,049 T2DM patients ...
1 Department of Information Technology and Computer Science, School of Computing and Mathematics, The Cooperative University of Kenya, Nairobi, Kenya. 2 Department of Computing and Informatics, School ...
Background Early warning systems (EWS) used across the world typically assign a fixed number of points to patients receiving supplemental oxygen, regardless of amount. This ordinal binary approach may ...
Objectives To systematically review all prediction models developed or validated for cancer therapy related cardiac dysfunction (CTRCD) and to quantitatively analyse their performance. Design ...
Copyright: © 2026 The Author(s). Published by Elsevier Ltd. Among 51,838 patients (mean age 63.8 years; 57% male), 21,091 (40.7%) experienced restraint. Use ...
New research from the US indicates that fine-tuning an AI foundation model on your own data does not need to reduce or impair the functionality of the original model – and that a relatively simple fix ...
This study aimed to develop and validate a computed tomography angiography based machine learning model that uses plaque composition data and degree of carotid stenosis to detect symptomatic carotid ...
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