Results 91 to 100 of about 1,502,113 (258)
Advanced Science, EarlyView.Interpretable machine learning reveals how composition and processing govern the formation and microstructural burden of Fe‐rich intermetallic compounds in recycled Al–Si–Fe–Mn alloys. By separating morphology selection from morphology‐conditioned burden partitioning, this framework shows that identical Fe contents can yield different intermetallic ...
Jaemin Wang +2 more
wiley +1 more source
Improving How Microsoft Excel Displays Default Extremely Small Probability Values
Spreadsheets in Education, 2012 Microsoft Excel™’s default method of displaying probability values observed in the sample, in the case of very small values, is confusing to beginning students in statistics.
David A. Larson, Sylvia E. Rogers
doaj +2 more sources
Mortgage Default Rates and Borrower Race [PDF]
We estimate a mortgage default model with national data on conventional mortgages that were current from 1986 to 1992. Our analysis confirms the results of previous analyses of Federal Housing Authority mortgages: Black households have higher marginal ...
Richard Anderson, James VanderHoff
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Polarization Dynamics in Ferroelectrics: Insights Enabled by Machine Learning Molecular Dynamics
Advanced Science, EarlyView.Machine learning molecular dynamics is presented as a route to capture polarization switching, domain wall kinetics, topological polar textures, and polar mechanical coupling beyond the limits of conventional atomistic methods. This Perspective surveys recent progress and identifies key methodological directions, including long‐range electrostatics ...
Dongyu Bai +3 more
wiley +1 more source
Sovereign risk in a structural approach: Evaluating sovereign ability-to-pay and probability of default [PDF]
We quantify the probability that a sovereign defaults on repayment obligations in foreign currency. Adopting the structural approach as first introduced by Merton, we consider the sovereigns ability-to-pay, characterised by the sum of discounted future ...
Maltritz, Dominik, Karmann, Alexander
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Advanced Science, EarlyView.Autonomous laboratories can now synthesize materials faster than experts can interpret the resulting diffraction data. A probabilistic framework combines refinement‐fit metrics with large language model‐derived chemical reasoning to rank competing phase interpretations and flag those unsuitable for autonomous use.
Olympia Dartsi +7 more
wiley +1 more source
Title from cover.Mode of access: Internet.Merger of: Official cohort default rate guide, and: Draft cohort default rate ...
United States. Dept. of Education. Default Management Division.
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A Model of Mortgage Default [PDF]
This paper solves a dynamic model of a household's decision to default on its mortgage, taking into account labor income, house price, inflation, and interest rate risk.
John Y. Campbell, João F. Cocco
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A Generative Neuro‐Symbolic AI for Protein Sequence Design
Advanced Science, EarlyView.We introduce EffieDes, a neuro‐symbolic framework coupling deep learning‐based fitness landscape parameterization with exact automated reasoning. Unlike greedy sampling, EffieDes identifies sequences that globally optimize fitness while satisfying intricate design constraints.
Marianne Defresne +12 more
wiley +1 more source
A Causal Framework for Credit Default Theory [PDF]
Most existing credit default theories do not link causes directly to the effect of default and are unable to evaluate credit risk in a rapidly changing market environment, as experienced in the recent mortgage and credit market crisis. Causal theories of
Wilson Sy
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