Results 211 to 220 of about 594,136 (249)

Compact Modeling of Volatile‐Switching Electrochemical Metallization Memory Cells by Means of the Electromotive Force

open access: yesAdvanced Intelligent Systems, EarlyView.
A volatile‐switching compact model of electrochemical metallization memory cells for neuromorphic architecture is developed and validated by reliable reproduction of device characterization measurements: I−V sweeps, SET kinetics, relaxation dynamics.
Rana Walied Ahmad   +4 more
wiley   +1 more source

[Improving record linkage for health research-how to overcome deficiencies?] [PDF]

open access: yesBundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz
Intemann T   +25 more
europepmc   +1 more source

QS4D: Quantization‐Aware Training for Efficient Hardware Deployment of Structured State‐Space Sequential Models

open access: yesAdvanced Intelligent Systems, EarlyView.
Quantization‐aware training creates resource‐efficient structured state space sequential S4(D) models for ultra‐long sequence processing in edge AI hardware. Including quantization during training leads to efficiency gains compared to pure post‐training quantization.
Sebastian Siegel   +5 more
wiley   +1 more source

Intervertebral disc degeneration affects the flexibility but not the vulnerability of the cervical spine - An in vitro study

open access: yesBrain and Spine
C. Liebsch   +5 more
doaj   +1 more source

A Flexible and Energy‐Efficient Compute‐in‐Memory Accelerator for Kolmogorov–Arnold Networks

open access: yesAdvanced Intelligent Systems, EarlyView.
This article presents KA‐CIM, a compute‐in‐memory accelerator for Kolmogorov–Arnold Networks (KANs). It enables flexible and efficient computation of arbitrary nonlinear functions through cross‐layer co‐optimization from algorithm to device. KA‐CIM surpasses CPU, ASIC, VMM‐CIM, and prior KAN accelerators by 1–3 orders of magnitude in energy‐delay ...
Chirag Sudarshan   +6 more
wiley   +1 more source

T1w/T2w Ratio Identifies the Basolateral Amygdala as a Preferential Target in Autoimmune Limbic Encephalitis. [PDF]

open access: yesJ Neuroimaging
Dadarwal R   +12 more
europepmc   +1 more source

Comparing the Latent Features of Universal Machine‐Learning Interatomic Potentials

open access: yesAdvanced Intelligent Systems, EarlyView.
This study quantitatively assesses how universal machine‐learning interatomic potentials encode the chemical space into latent features, showing unique model‐specific representations with high cross‐model reconstruction errors. It explores how training datasets, protocols, and targets affect these encodings.
Sofiia Chorna   +5 more
wiley   +1 more source

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