Results 11 to 20 of about 485 (89)
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 +9 more
wiley +1 more source
A machine learning method, opt‐GPRNN, is presented that combines the advantages of neural networks and kernel regressions. It is based on additive GPR in optimized redundant coordinates and allows building a representation of the target with a small number of terms while avoiding overfitting when the number of terms is larger than optimal.
Sergei Manzhos, Manabu Ihara
wiley +1 more source
Overcoming the Nyquist Limit in Molecular Hyperspectral Imaging by Reinforcement Learning
Explorative spectral acquisition guide automatically selects informative spectral bands to optimize downstream tasks, outperforming full‐spectrum acquisition. The selected hyperspectral data are used for tasks such as unmixing and segmentation. BandOptiNet encodes selection states and outputs optimal bands to guide spectral acquisition. Recent advances
Xiaobin Tang +4 more
wiley +1 more source
Timeline of key academic milestones and individuals that shaped chemical engineering at FQ‐UNAM and in Mexico. Abstract One hundred years after the beginning of the teaching of Chemical Engineering in Mexico, which started in 1925 in the former National School of Chemical Sciences, currently Faculty of Chemistry (FQ) at National Autonomous University ...
Patricia Pérez‐Salinas +2 more
wiley +1 more source
A Non‐Parametric Framework for Correlation Functions on Product Metric Spaces
Summary We propose a non‐parametric framework for analysing data defined over products of metric spaces, a versatile class encountered in various fields. This framework accommodates non‐stationarity and seasonality and is applicable to both local and global domains, such as the Earth's surface, as well as domains evolving over linear time or time ...
Pier Giovanni Bissiri +3 more
wiley +1 more source
Reinforcement Learning for Jump‐Diffusions, With Financial Applications
ABSTRACT We study continuous‐time reinforcement learning (RL) for stochastic control in which system dynamics are governed by jump‐diffusion processes. We formulate an entropy‐regularized exploratory control problem with stochastic policies to capture the exploration–exploitation balance essential for RL.
Xuefeng Gao, Lingfei Li, Xun Yu Zhou
wiley +1 more source
ABSTRACT Microbial volatile organic compounds (mVOCs) enable plants to perceive microbial activity prior to physical contact, yet the contribution of individual bacterial volatiles to immune signalling and disease resistance remains incompletely understood.
Ivan A. Paponov +6 more
wiley +1 more source
ABSTRACT Recent studies suggest that variations in milk yield during lactation can serve as a metric for assessing individual resilience, with minimum fluctuations reflecting greater resilience in cows. With automatic milking systems, multiple records can be obtained from many cows on a daily basis. Given that animals are continually exposed to a range
M. Agyiri +7 more
wiley +1 more source
Abstract Pedro de Ayala served as a diplomat for King Ferdinand II of Aragon and Queen Isabella I of Castile at the courts of Henry VII, King of England, and James IV, King of Scots. In July 1498, he wrote a letter, partly in cipher, to report to his king and queen on such matters as Spain's interests in international diplomacy; the characters and ...
Adrian William Jaime +2 more
wiley +1 more source
Abstract BACKGROUND The temporal sequence of clinical, imaging, and biological changes in sporadic frontotemporal lobar degeneration (FTLD)–associated syndromes remains poorly characterized, and a comprehensive biomarker cascade model is lacking. METHODS We developed a data‐driven biomarker cascade model in 489 patients across the FTLD spectrum (211 ...
Alberto Benussi +15 more
wiley +1 more source

