Results 71 to 80 of about 33,205 (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
wiley   +1 more source

The Efficacy of Intracanal Medicaments Within the Regenerative Endodontic Procedures on Permanent Necrotic Immature Teeth: Systematic Review and Naïve Indirect‐Comparison Meta‐Analysis

International Endodontic Journal, EarlyView.
ABSTRACT Objectives The objectives of this study were to estimate and compare the 1‐year clinical success rates of triple antibiotic paste (TAP), double antibiotic paste (DAP), calcium hydroxide (CH) within regenerative endodontic procedures (REPs) on permanent necrotic immature teeth.
Mario Alovisi, Paolo G. Arduino, Stefano Petti   +2 more
wiley   +1 more source

A Comparison between Wasserstein Distance and a Distance Induced by Fisher-Rao Metric in Complex Shapes Clustering

Proceedings, 2017
Shape Analysis studies geometrical objects, as for example a flat fish in the plane or a human head in the space. The applications range from structural biology, computer vision, medical imaging to archaeology. We focus on the selection of an appropriate
Angela De Sanctis, Stefano A. Gattone
doaj   +1 more source

On Metric Choice in Dimension Reduction for Fréchet Regression

International Statistical Review, EarlyView.
Summary Fréchet regression is becoming a mainstay in modern data analysis for analysing non‐traditional data types belonging to general metric spaces. This novel regression method is especially useful in the analysis of complex health data such as continuous monitoring and imaging data.
Abdul‐Nasah Soale, Congli Ma, Siyu Chen, Obed Koomson   +3 more
wiley   +1 more source

An alternating multiple residual Wasserstein regularization model for Gaussian image denoising

Scientific Reports
Residual histograms can provide meaningful statistical information in low-level visual research. However, the existing image denoising methods do not deeply explore the potential of alternate multiple residual histograms for overall optimization ...
Ruiqiang He, Wangsen Lan, Yaojun Hao, Jianfang Cao, Fang Liu   +4 more
doaj   +1 more source

A Comparative Review of Specification Tests for Diffusion Models

International Statistical Review, EarlyView.
Summary Diffusion models play an essential role in modelling continuous‐time stochastic processes in the financial field. Therefore, several proposals have been developed in the last decades to test the specification of stochastic differential equations.
A. López‐Pérez, D. Diz‐Castro, M. Febrero‐Bande, W. González‐Manteiga   +3 more
wiley   +1 more source

Practical bounds on the error of Bayesian posterior approximations: A nonasymptotic approach

, 2018
Bayesian inference typically requires the computation of an approximation to the posterior distribution. An important requirement for an approximate Bayesian inference algorithm is to output high-accuracy posterior mean and uncertainty estimates ...
Broderick, Tamara, Campbell, Trevor, Huggins, Jonathan H., Kasprzak, Mikołaj   +3 more
core  

A Non‐Parametric Framework for Correlation Functions on Product Metric Spaces

International Statistical Review, EarlyView.
Summary We propose a non‐parametric framework for analysing data defined over products of metric spaces, a versatile class encountered in various fields. This framework accommodates non‐stationarity and seasonality and is applicable to both local and global domains, such as the Earth's surface, as well as domains evolving over linear time or time ...
Pier Giovanni Bissiri, Bernardo Nipoti, Emilio Porcu, Philip White   +3 more
wiley   +1 more source

Validation of machine learning based scenario generators

Journal of Risk and Insurance, EarlyView.
Abstract Machine learning (ML) methods are becoming increasingly important for designing economic scenario generators for internal models. Validating data‐driven models requires different methods than validating classical, theory‐based models. We discuss two novel aspects of such validation: first, checking the multivariate distribution of risk factors,
Gero Junike, Solveig Flaig, Ralf Werner
wiley   +1 more source

Two clusterings to capture basketball players’ shooting tendencies using tracking data: clustering of shooting styles and the shots themselves

International Journal of Computer Science in Sport
Studies to understand the shooting preferences of basketball players relied exclusively on data on shot location, which did not lead to concrete understandings because they contained no information on how they moved to that location.
Yamada Kazuhiro, Fujii Keisuke
doaj   +1 more source