Results 81 to 90 of about 24,182 (212)

Mapper Comparison with Wasserstein Metrics

, 2018
The challenge of describing model drift is an open question in unsupervised learning. It can be difficult to evaluate at what point an unsupervised model has deviated beyond what would be expected from a different sample from the same population. This is particularly true for models without a probabilistic interpretation. One such family of techniques,
openaire   +2 more sources

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

No-Reference Hyperspectral Image Quality Assessment via Ranking Feature Learning

Remote Sensing
In hyperspectral image (HSI) reconstruction tasks, due to the lack of ground truth in real imaging processes, models are usually trained and validated on simulation datasets and then tested on real measurements captured by real HSI imaging systems ...
Yuyan Li, Yubo Dong, Haoyong Li, Danhua Liu, Fang Xue, Dahua Gao   +5 more
doaj   +1 more source

Bridging classical data assimilation and optimal transport: the 3D-Var case [PDF]

Nonlinear Processes in Geophysics
Because optimal transport (OT) acts as displacement interpolation in physical space rather than as interpolation in value space, it can avoid double-penalty errors generated by mislocations of geophysical fields.
M. Bocquet, P. J. Vanderbecken, A. Farchi, J. Dumont Le Brazidec, Y. Roustan   +4 more
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

Metric extrapolation in the Wasserstein space

Calculus of Variations and Partial Differential Equations
In this article we study a variational problem providing a way to extend for all times minimizing geodesics connecting two given probability measures, in the Wasserstein space. This is simply obtained by allowing for negative coefficients in the classical variational characterization of Wasserstein barycenters.
Gallouët, Thomas, Natale, Andrea, Todeschi, Gabriele   +2 more
openaire   +4 more sources

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

The Wasserstein Metric between a Discrete Probability Measure and a Continuous One

Mathematics
This paper examines the Wasserstein metric between the empirical probability measure of n discrete random variables and a continuous uniform measure in the d-dimensional ball, providing an asymptotic estimation of their expectations as n approaches ...
Weihua Yang, Xu Zhang, Xia Wang
doaj   +1 more source

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

On a class of norms generated by nonnegative integrable distributions

Dependence Modeling, 2019
We show that any distribution function on ℝd with nonnegative, nonzero and integrable marginal distributions can be characterized by a norm on ℝd+1, called F-norm. We characterize the set of F-norms and prove that pointwise convergence of a sequence of F-
Falk Michael, Stupfler Gilles
doaj   +1 more source