Results 71 to 80 of about 33,807 (240)

A Markov approach to credit rating migration conditional on economic states

Canadian Journal of Statistics, EarlyView.
Abstract We develop a model for credit rating migration that accounts for the impact of economic state fluctuations on default probabilities. The joint process for the economic state and the rating is modelled as a time‐homogeneous Markov chain. While the rating process itself possesses the Markov property only under restrictive conditions, methods ...
Michael Kalkbrener, Natalie Packham
wiley   +1 more source

Location Dependent Dirichlet Processes

, 2017
Dirichlet processes (DP) are widely applied in Bayesian nonparametric modeling. However, in their basic form they do not directly integrate dependency information among data arising from space and time.
A Oliva, A Rodríguez, C Bishop, C Williams, CE Rasmussen, D Blei, D Blei, D Dunson, E Sudderth, F Zhu, H Ishwaran, J Duan, J Griffin, J Griffin, J Paisley, J Sethuraman, J Shi, L Ren, N Foti, P Orbanz, R Unnikrishnan, S Kumar, T Ferguson, X Sun, YW Teh   +24 more
core   +1 more source

Microscopic time‐dependent mechanical behavior of shale derived from nanoindentation

Deep Underground Science and Engineering, EarlyView.
This study conducted grid nanoindentation creep tests to systematically analyze the microscopic creep behaviors of shale. Based on the analysis of creep strain rate sensitivity, the primary mechanism of microscopic creep in shale was found to be the extension and closure of microcracks.
Cunbao Li, Shilei Zhong, Heping Xie, Changtai Zhou, Jianjun Hu   +4 more
wiley   +1 more source

FLARE-GMM: an automatic aerosol typing model based on Mie–Raman–fluorescence lidar measurements with LILAS [PDF]

Atmospheric Measurement Techniques
This study presents the development of an automated aerosol typing model utilizing Mie–Raman–fluorescence lidar data collected by LILAS (Lille Lidar for Atmospheric Study), located on the ATOLL (ATmospheric Observations at LiLLe) platform in Lille ...
R. Miri, O. Pujol, Q. Hu, P. Goloub, I. Veselovskii, I. Veselovskii, T. Podvin, F. Ducos   +7 more
doaj   +1 more source

Rhythms in longitudinal thalamic recordings are linked to seizure risk

Epilepsia, EarlyView.
Abstract Objective Seizure unpredictability remains a major clinical challenge for people with epilepsy. Previous works have shown that seizure risk is associated with circadian and multi‐day cycles in both brain and physiological signals. However, it remains unclear whether neural activity from deep brain structures such as the anterior nucleus of the
Xinbing Zhang, Zachary T. Sanger, Thomas Lisko, Steffen Ventz, Robert A. McGovern, Theoden I. Netoff   +5 more
wiley   +1 more source

GMM-IKRS: Gaussian Mixture Models for Interpretable Keypoint Refinement and Scoring

Accepted at ECCV ...
Emanuele Santellani, Martin Zach, Christian Sormann, Mattia Rossi, Andreas Kuhn, Friedrich Fraundorfer   +5 more
openaire   +2 more sources

Efficient Implementation Of Gmm Based Speaker Verification Using Sorted Gaussian Mixture Model

, 2006
Publication in the conference proceedings of EUSIPCO, Florence, Italy ...
Sadegh Mohammadi, Hamid, Saeidi, Rahim
openaire   +1 more source

AI‐based localization of the epileptogenic zone using intracranial EEG

Epilepsia Open, EarlyView.
Abstract Artificial intelligence (AI) is rapidly transforming our lives. Machine learning (ML) enables computers to learn from data and make decisions without explicit instructions. Deep learning (DL), a subset of ML, uses multiple layers of neural networks to recognize complex patterns in large datasets through end‐to‐end learning.
Atsuro Daida, Yipeng Zhang, Sotaro Kanai, Richard Staba, Vwani Roychowdhury, Hiroki Nariai   +5 more
wiley   +1 more source

A Multivariate Mixed‐Effects Regression Framework for Ground Motion Modeling: Integrating Parametric and Machine Learning Approaches

Earthquake Engineering &Structural Dynamics, EarlyView.
ABSTRACT Multivariate ground motion models (GMMs) that capture the correlation between different intensity measures (IMs) are essential for seismic risk assessment. Conventional GMMs are often developed using a two‐stage approach, where separate univariate models with predefined functional forms are fitted first, and correlation is addressed in a ...
Sayed Mohammad Sajad Hussaini, Shaghayegh Karimzadeh, Paulo B. Lourenço   +2 more
wiley   +1 more source

An Electromyographic‐Based Control Using Gaussian Mixture Model on an Upper‐Limb Cable‐Driven Rehabilitation Robot

Advanced Intelligent Systems
Electromyographic (EMG)‐based admittance control by arm force can provide continuous motion control in robot‐assisted rehabilitation. Natural and complex physical human–robot interactions utilizing intelligent EMG‐based interfaces require a computational
Jianlin Zheng, Zhijun Li, Ting Xu, Rong Song   +3 more
doaj   +1 more source