Results 121 to 130 of about 1,473,129 (216)

Machine learning approaches in automated infant General Movements Assessment: A scoping review

open access: yesDevelopmental Medicine &Child Neurology, EarlyView.
Automated infant General Movements Assessment increasingly uses machine‐ and deep‐learning approaches to classify movement patterns and estimate cerebral palsy risk from video or sensor data. This scoping review highlights how dataset characteristics, recording environment, pose‐estimation accuracy, feature extraction, and model design influence system
Manpreet Kaur   +4 more
wiley   +1 more source

Missing Values in Time Series: A Brief Review and a New Versatile Imputation Method

open access: yesInternational Statistical Review, EarlyView.
Summary Missing data can significantly hamper standard time series analysis, yet they occur frequently in applications. In this paper, we briefly review some available methods for handling missing values and introduce the temporal Wasserstein imputation, a novel method for imputing missing data in time series.
Shuo‐Chieh Huang   +2 more
wiley   +1 more source

Market Making With Fads, Informed, and Uninformed Traders

open access: yesMathematical Finance, EarlyView.
ABSTRACT We characterize the solution to a continuous‐time optimal liquidity provision problem in a market populated by informed and uninformed traders. In our model, the asset price exhibits fads —these are short‐term deviations from the fundamental value of the asset.
Emilio Barucci   +2 more
wiley   +1 more source

Inflation Inequality Across Household Income Groups in Brazil: Persistence, Trend and Volatility

open access: yesThe Manchester School, EarlyView.
ABSTRACT This article investigates inflation inequality across four income strata in Brazil (very low, low, middle, and high income) from July 2006 to April 2025, using the Headline IPCA as a benchmark. We test the hypothesis that inflation dynamics and transmission mechanisms are structurally unequal and disproportionately affect lower‐income ...
Sinara do Valle, Cleomar Gomes da Silva
wiley   +1 more source

Economic Growth Vulnerability Across Euro Area Countries

open access: yesOxford Bulletin of Economics and Statistics, EarlyView.
ABSTRACT We analyse growth vulnerability in the four largest Euro Area (EA) economies, measured as a lower quantile of the growth distribution conditional on EA‐wide and country‐specific macroeconomic/financial factors. Growth densities are obtained under a normal activity scenario and under stressed conditions.
Claudio Lissona, Esther Ruiz
wiley   +1 more source

Simple and extended Kalman filters : an application to term structures of commodity prices. [PDF]

open access: yes
This article presents and compares two different Kalman filters. These methods provide a very interesting way to cope with the presence of non-observable variables, which is a frequent problem in finance. They are also very fast even in the presence of a
Lautier, Delphine, Galli, Alain
core  

Map‐Matching With Recursive Bayes Filter and Context‐Dependent Transition Dynamics for Scene Modeling in Automated Driving

open access: yesProceedings in Applied Mathematics and Mechanics, Volume 26, Issue 4, December 2026.
ABSTRACT We present an efficient multi‐object map‐matching approach for scene modeling in the context of automated driving. The mapping of traffic participants to the road topology is a key component of the scene modeling step in the processing pipeline for situation‐aware automated driving.
Maximilian Gerwien, Klaus Röbenack
wiley   +1 more source

Improved Frequency-selective Filters [PDF]

open access: yes
This paper gives an account of some techniques for designing recursive frequency-selective filters which can be applied to data sequences of limited duration which may be nonstationary.
Stephen Pollock
core  

Few Shot Learning for Flame State Monitoring From Limited Visible and Infrared Images

open access: yesExpert Systems, Volume 43, Issue 11, November 2026.
ABSTRACT The success of machine learning in image‐based combustion monitoring requires big data, which is costly, and even impossible in industrial applications. To address this, we introduce metric‐based few shot learning for combustion monitoring and classification, to the best of our knowledge, for the first time.
Ruiyuan Kang   +2 more
wiley   +1 more source

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