Results 251 to 260 of about 15,911,760 (295)

A Dual‐Branch Flux‐Based Extended Memristor Model With Machine‐Learning‐Assisted Calibration

open access: yesAdvanced Electronic Materials, EarlyView.
Multilayer oxide memristors integrated in crossbar arrays are described through a dual‐branch, flux‐controlled compact model. A three‐stage calibration workflow combining Latin hypercube sampling, Bayesian optimization, and gradient‐based refinement extracts device parameters from experimental data.
Davide Rossetti   +6 more
wiley   +1 more source

Integrating Automated Electrochemistry and High‐Throughput Characterization with Machine Learning to Explore Si─Ge─Sn Thin‐Film Lithium Battery Anodes

open access: yesAdvanced Energy Materials, Volume 15, Issue 11, March 18, 2025.
A closed‐loop, data‐driven approach facilitates the exploration of high‐performance Si─Ge─Sn alloys as promising fast‐charging battery anodes. Autonomous electrochemical experimentation using a scanning droplet cell is combined with real‐time optimization to efficiently navigate composition space.
Alexey Sanin   +7 more
wiley   +1 more source

Quantifying target antigen-dependent CAR T-cell performance against AML. [PDF]

open access: yesCancer Cell Int
Shah S   +7 more
europepmc   +1 more source

Bayesian Post-Model-Selection Estimation

IEEE Signal Processing Letters, 2021
Estimation after model selection refers to the problem where the exact observation model is unknown and is assumed to belong to a set of candidate models. Thus, a data-based model-selection stage is performed prior to the parameter estimation stage, which affects the performance of the subsequent estimation.
Nadav Harel, Tirza Routtenberg
openaire   +1 more source

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