Results 71 to 80 of about 125,567 (253)
ergm.graphlets: A Package for ERG Modeling Based on Graphlet Statistics
Journal of Statistical Software, 2015 Exponential-family random graph models are probabilistic network models that are parametrized by sufficient statistics based on structural (i.e., graph-theoretic) properties. The ergm package for the R statistical computing environment is a collection of
Ömer Nebil Yavero?lu +5 more
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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
Second-order asymptotics for discriminant analysis in exponential family
Lietuvos Matematikos Rinkinys, 1999 There is not abstract.
Kęstutis Dučinskas
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Likelihood Ratio Exponential Families
CoRR, 2020 The exponential family is well known in machine learning and statistical physics as the maximum entropy distribution subject to a set of observed constraints, while the geometric mixture path is common in MCMC methods such as annealed importance sampling.
Rob Brekelmans +4 more
openaire +2 more sources
Advanced Materials, EarlyView.Magnetic particles are organized into layered architectures by combining shear flow and magnetic fields, with the resulting structures governed by appropriate Mason numbers. The programmed assemblies provide spatial guidance for cell placement, linking field‐controlled self‐assembly, flow‐induced structuring and biological organization.
Guillermo Camacho +5 more
wiley +1 more source
T-Transmuted X Family of Distributions
Statistica, 2018 Using the quadratic transmutation map (QRTM) approach of Shaw and Buckley (2007) and the T -X family method by Alzaatreh et al. (2013b), we have developed a new family of distributions called T -transmuted X family of distributions.
Girish Babu Moolath, Jayakumar K
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Advanced Materials, EarlyView.This work develops bias‐triggered conductivity relaxation as a novel technique to study oxygen reactions in mixed ionic‐electronic conducting thin films by integrating electrochemical titration and electrical conductivity relaxation to achieve synchronous multi‐parameter characterization, providing simultaneous electronic, ionic, and extraordinarily ...
Alexander Stangl +4 more
wiley +1 more source
Recent Advances in Ferrite‐Based Materials for Biomedical Applications: A Comprehensive Review
Advanced Materials, EarlyView.Ferrite nanoplatforms are presented as tunable biomedical materials in which synthesis control, cation engineering, defect/morphology regulation, and surface functionalization govern structure–property–bioactivity relationships. These design strategies enable multifunctional applications including MRI contrast, magnetic hyperthermia, targeted drug ...
Pramod D. Mhase +6 more
wiley +1 more source
Advanced Materials Interfaces, EarlyView.Large size (∼100 µm) monolayer MoS2 grown by LPI‐CVD on n‐GaN exhibit a high n‐type doping, very low strain, and a type‐I band alignment at MoS2/GaN interface. Photocurrent measurements under illumination with photon energies from ∼2 to ∼5 eV show superior electro‐optical performances of these MoS2/n‐GaN heterojunctions as compared to Ni/n‐GaN devices ...
Salvatore Ethan Panasci +12 more
wiley +1 more source
Advanced Materials Technologies, EarlyView.ABSTRACT Molybdenum disulfide (MoS2) has attracted attention as a promising material due to the growing demand for environmentally friendly, cost‐effective, and efficient water treatment techniques. With its physicochemical characteristics, this stratified bidimensional material allows it to be highly effective in adsorption and catalytic performance ...
Pariksha Bishnoi +4 more
wiley +1 more source