Results 231 to 240 of about 2,854,398 (286)

Automated data-driven discovery of material models based on symbolic regression: A case study on the human brain cortex. [PDF]

Acta Biomater
Hou J, Chen X, Wu T, Kuhl E, Wang X.
europepmc   +1 more source

People Counting and Positioning Using Low‐Resolution Infrared Images for FeFET‐Based In‐Memory Computing

Advanced Electronic Materials, EarlyView.
In this work, low‐resolution infrared imaging is combined with a 28 nm FeFET IMC architecture to enable compact, energy‐efficient edge inference. MLC FeFET devices are experimentally characterized, and controlled multi‐level current accumulation is validated at crossbar array level.
Alptekin Vardar, Li Zhang, Alexander Rehmer, Marc Lupp, Subhashree Baskaran, Osama Abdelaal, Franz Müller, Nandakishor Yadav, Bing Li, Thomas Kämpfe   +9 more
wiley   +1 more source

Sensitivity analysis of parameters for carbon sequestration: Symbolic regression models based on open porous media reservoir simulators predictions. [PDF]

Heliyon
Praks P, Rasmussen A, Lye KO, Martinovič J, Praksová R, Watson F, Brkić D.   +6 more
europepmc   +1 more source

Silicon Nitride Resistive Memories

Advanced Electronic Materials, EarlyView.
Amorphous SiNx is an attractive resistance switching material for ReRAM applications due to its physicochemical properties, such as humidity resistance, low oxygen diffusivity, and is used as a metal diffusion blocker. By modifying the ratio between N and Si atoms, the microstructure of the SiNx is affected, rendering it possible to change the ...
Alexandros‐Eleftherios Mavropoulis, Nikolaos Vasileiadis, Iosif‐Angelos Fyrigos, Emmanouil Stavroulakis, Caroline Bonafos, Pascal Normand, Georgios Ch. Sirakoulis, Panagiotis Dimitrakis   +7 more
wiley   +1 more source

Assessing perioperative risks in a mixed elderly surgical population using machine learning: A multi-objective symbolic regression approach to cardiorespiratory fitness derived from cardiopulmonary exercise testing. [PDF]

PLOS Digit Health
Arina P, Ferrari D, Kaczorek MR, Tetlow N, Dewar A, Stephens R, Martin D, Moonesinghe R, Singer M, Whittle J, Mazomenos EB.   +10 more
europepmc   +1 more source

The Influence of Residual Ion Drift During Programming of Chip‐Integrated Nanoscale HfO2‐Based Memristive Devices

Advanced Electronic Materials, EarlyView.
1T1R‐arrays combining filamentary‐type memristors and CMOS transistors offer great potential for energy‐efficient analog hardware accelerators. Here, transient SET analysis of nanoscale HfO2 memristors integrated on 180 nm CMOS wafers is discussed.
Oliver Artner, Felix Cüppers, Seokki Son, Yang Chen, Xiaohua Liu, Christopher Bengel, Dennis Nielinger, André Zambanini, Stefan Wiefels, Stephan Menzel, Regina Dittmann, Susanne Hoffmann‐Eifert   +11 more
wiley   +1 more source

Learning pharmacometric covariate model structures with symbolic regression networks. [PDF]

J Pharmacokinet Pharmacodyn
Wahlquist Y, Sundell J, Soltesz K.
europepmc   +1 more source

Artificial Intelligence for Fluorite Ferroelectric Materials: From Discovery to Optimization

Advanced Electronic Materials, EarlyView.
Artificial intelligence accelerates the discovery and optimization of HfO2‐based fluorite ferroelectrics by linking synthesis, structure, properties, and device performance. Machine learning, deep‐learning analysis, and AI‐driven atomistic modeling enable predictive design, dopant screening, and closed‐loop optimization toward next‐generation ...
Faizan Ali, David Lehninger, Florencio Sánchez, Ignasi Fina   +3 more
wiley   +1 more source

Symbolic Regression with Neural Symbolic Networks

This paper introduces a novel approach to symbolic regression, termed Neural Symbolic Networks (NSNs), designed to overcome the limitations of traditional neural networks in representing complex mathematical relationships. The core idea is to integrate the strengths of both neural networks and symbolic regression techniques.
openaire   +1 more source

LogicGep: Boolean networks inference using symbolic regression from time-series transcriptomic profiling data. [PDF]

Brief Bioinform
Zhang D, Gao S, Liu ZP, Gao R.
europepmc   +1 more source