Results 111 to 120 of about 323,408 (293)
Organic Materials of Tomorrow: Horizons of Artificial Intelligence
Advanced Materials, EarlyView.This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena +3 more
wiley +1 more source
Supervising Unsupervised Learning
CoRR, 2017 We introduce a framework to leverage knowledge acquired from a repository of (heterogeneous) supervised datasets to new unsupervised datasets. Our perspective avoids the subjectivity inherent in unsupervised learning by reducing it to supervised learning, and provides a principled way to evaluate unsupervised algorithms.
Vikas K. Garg 0001, Adam Kalai
openaire +2 more sources
“Smelltronics”—From Gas to Smell Sensing
Advanced Materials, EarlyView.The emerging field of smelltronics, encompassing sensing technologies for complex volatile organic compounds, holds significant potential for extracting valuable chemical information. It facilitates the noninvasive, real‐time monitoring of humans, food, and the environment.
Takeshi Ono +7 more
wiley +1 more source
burkh4rt/Unsupervised-Multimodal-Trajectory-Modeling: 2023.1
, 2023 as released: https://pypi.org/project/unsupervised-multimodal-trajectory-modeling/2023 ...
Michael Burkhart
core +1 more source
Advanced Materials, EarlyView.Mixed‐cation lead mixed‐halide perovskites suffer from structural instabilities linked to nanoscale heterogeneity. To probe this non‐destructively, a low‐dose, concurrent 4D‐STEM and EDX methodology has been developed. Examining a (FA0.83Cs0.17)Pb(I0.8Br0.2)3 film revealed a complex mosaic of coexisting crystal structures. Crucially, local deficiencies
Jinseok Ryu +6 more
wiley +1 more source
Advanced Materials Interfaces, EarlyView.This work critically reviews MXenes as highly effective multifunctional nanomaterials for the adsorption of radio‐contaminants, demonstrating a remarkable adsorption capacity of up to 1376.75 mg/g and cyclic stability of 2–8 cycles, with complexation, electrostatic interactions, and the numerical strength of MXene active sites playing a key operational
Stephen Sunday Emmanuel +1 more
wiley +1 more source
Unsupervised learning of shape manifolds [PDF]
, 2007 Classical shape analysis methods use principal component analysis to reduce the dimensionality of shape spaces. The basic assumption behind these methods is that the subspace corresponding to the major modes of variation for a particular class of shapes ...
Bhalerao, Abhir +5 more
core +1 more source
On‐Chip Photonic Neural Network Architectures
Advanced Optical Materials, EarlyView.This review presents a comprehensive overview of on‐chip photonic neural network architectures, covering key photonic building blocks, representative network types, and emerging applications. Recent advances, implementation challenges, and future directions are examined, highlighting the potential of integrated photonics to enable ultrafast, energy ...
Seokjin Hong +7 more
wiley +1 more source
Hierarchical Clustering for Anomalous Traffic Conditions Detection in Power Substations
Ciencia e Ingeniería Neogranadina, 2019 The IEC 61850 standard has contributed significantly to the substation management and automation process by incorporating the advantages of communications networks into the operation of power substations.
Erwin Alexander Leal Piedrahita
doaj
Deep Temporal Joint Clustering for Satellite Image Time-Series Analysis
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingWith the advancement of remote sensing satellite technology, the acquisition of Satellite Image Time-Series (SITS) data has significantly increased, providing new opportunities and challenges for land cover analysis.
Wenqi Guo +5 more
doaj +1 more source