Results 71 to 80 of about 6,372,670 (283)
Priors in Bayesian Learning of Phonological Rules [PDF]
, 2004 This paper describes a Bayesian procedure for unsupervised learning of phonological rules from an unlabeled corpus of training data. Like Goldsmith's Linguistica program (Goldsmith, 2004b), whose output is taken as the starting point of this procedure ...
Johnson, Mark +3 more
core +1 more source
“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
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
Learning by Unsupervised Nonlinear Diffusion
CoRR, 2018 40 Pages, 17 ...
Mauro Maggioni, James M. Murphy
openaire +4 more sources
Towards Open Ended Learning: Budgets, Model Selection, and Representation [PDF]
, 2011 Biological organisms learn to recognize visual categories continuously over the course of their lifetimes. This impressive capability allows them to adapt to new circumstances as they arise, and to flexibly incorporate new object categories as they are ...
Gomes, Ryan Geoffrey
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
Adversarial Robustness on Image Classification With
IEEE AccessAttacks and defences in adversarial machine learning literature have primarily focused on supervised learning. However, it remains an open question whether existing methods and strategies can be adapted to unsupervised learning approaches.
Rollin Omari, Junae Kim, Paul Montague
doaj +1 more source
Unsupervised Learning Bioreactor Regimes [PDF]
Computers & Chemical EngineeringEfficient bioreactor operation is essential for biomanufacturing success. Traditional Computational Fluid Dynamics (CFD) simulations are detailed but slow and complex, limiting their use in real-time applications. This study introduces a novel unsupervised learning algorithm that clusters bioreactors into coherent regions using CFD-generated data, with
Víctor Puig I Laborda +4 more
openaire +4 more sources
SAGES: Scalable Attributed Graph Embedding With Sampling for Unsupervised Learning
, 2023 Unsupervised graph embedding method generates node embeddings to preserve structural and content features in a graph without human labeling burden. However, most unsupervised graph representation learning methods suffer issues like poor scalability or ...
Wang, Jialin +5 more
core +1 more source