Results 81 to 90 of about 280 (174)
Establishing Shape Correspondences: A Survey
Computer Graphics Forum, EarlyView.Abstract Shape correspondence between surfaces in 3D is a central problem in geometry processing, concerned with establishing meaningful relations between surfaces. While all correspondence problems share this goal, specific formulations can differ significantly: Downstream applications require certain properties that correspondences must satisfy ...
A. Heuschling, H. Meinhold, L. Kobbelt
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Advances in 4D Representation: Geometry, Motion, and Interaction
Computer Graphics Forum, EarlyView.We survey 4D representation through three key pillars — geometry, motion, and interaction — offering a selective, representation‐centric perspective to guide researchers in choosing and customizing the right 4D representation for their tasks. Abstract We present a survey on 4D generation and reconstruction, a fast‐evolving subfield of computer graphics
M. Zhao +7 more
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Monetary Policy When Preferences Are Quasi‐Hyperbolic
Journal of Money, Credit and Banking, EarlyView.Abstract We study discretionary monetary policy in an economy where economic agents have quasi‐hyperbolic discounting. We demonstrate that a benevolent central bank is able to keep inflation under control for a wide range of discount factors. If the central bank, however, does not adopt the household's time preferences and tries to discourage early ...
RICHARD DENNIS, OLEG KIRSANOV
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Digital range of motion analysis is sensitive to subjective steps in joint model construction
Journal of Anatomy, EarlyView.A systematic sensitivity analysis of a six degree‐of‐freedom range of motion (ROM) analysis workflow was conducted to evaluate how variation in the subjective steps of the reference pose assembly affects the determined viable poses in the ankle and tarsometatarsophalangeal III joints of Guinea fowl (Numida meleagris).
R. J. Lowes +4 more
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Solving Stochastic Climate‐Economy Models: A Deep Least‐Squares Monte Carlo Approach
Mathematical Finance, EarlyView.ABSTRACT Stochastic versions of recursive integrated climate‐economy assessment models are essential for studying and quantifying policy decisions under uncertainty. However, as the number of state variables and stochastic shocks increases, solving these models via deterministic grid‐based dynamic programming (e.g., value‐function iteration/projection ...
Aleksandar Arandjelović +4 more
wiley +1 more source
Meteoritics &Planetary Science, EarlyView.Abstract We investigated the structural framework of the north–northwestern Paraná Basin in Brazil to test whether the pre‐impact structures in this region may have had any influence on the first‐order formation and morphostructure of the Araguainha impact structure (AIS).
Renato B. Bernardes +5 more
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On the degenerate (h,q) $(h,q)$-Changhee numbers and polynomials
Journal of Inequalities and Applications, 2019 The Changhee numbers and polynomials are introduced by Kim, Kim and Seo (Adv. Stud. Theor. Phys. 7(20):993–1003, 2013), and the generalizations of those polynomials are characterized.
Yunjae Kim, Jin-Woo Park
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, 2021 In this paper, by introducing the degenerate Fubini-type polynomials, we give several relations with the help of the Faà di Bruno formula and some properties of Bell polynomials, and generating function methods. Also, we derive some new explicit formulas and recurrence relations for Fubini-type polynomials and numbers. Associating the degenerate Fubini-
openaire +2 more sources
Likelihood Estimation for Stochastic Differential Equations with Mixed Effects
Scandinavian Journal of Statistics, EarlyView.ABSTRACT Stochastic differential equations provide a powerful tool for modelling dynamic phenomena affected by random noise. When time series are observed for several experimental units, it is often the case that some of the parameters vary between the individual experimental units.
Fernando Baltazar‐Larios +2 more
wiley +1 more source
Using DSGE and Machine Learning to Forecast Public Debt for France
Journal of Forecasting, Volume 45, Issue 5, Page 2173-2185, August 2026.ABSTRACT Forecasting public debt is essential for effective policymaking and economic stability, yet traditional approaches face challenges due to data scarcity. While machine learning (ML) has demonstrated success in financial forecasting, its application to macroeconomic forecasting remains underexplored, hindered by short historical time series and ...
Emmanouil Sofianos +4 more
wiley +1 more source