Publications related to Explained variation

What drives electricity tariffs in Switzerland? Two-stage statistical and geospatial analysis of structural differences across 1913 municipalities

Yael Frischholz, Noémie Alice Yvonne Ségolène Jeannin, Fabian Heymann

We present a two-staged statistical and geospatial analysis exploring the discrepancies of household electricity tariffs across 1,913 Swiss municipalities. First, we perform a multilinear regression analysis, considering structural, sociodemographic data a ...

2023

Characterization of high harmonic frequencies in reactor noise experiments within the CORTEX project

Andreas Pautz, Vincent Pierre Lamirand

We present a novel technique of neutron noise detection and experimental data interpretation developed during the EU H2020 project CORTEX aiming to improve the capabilities for identification and localization of neutron noise sources. The experimental data ...

2022

Evaluating the Explainers: Black-Box Explainable Machine Learning for Student Success Prediction in MOOCs

Vinitra Swamy, Bahar Radmehr, Mirko Marras, Natasa Krco

Neural networks are ubiquitous in applied machine learning for education. Their pervasive success in predictive performance comes alongside a severe weakness, the lack of explainability of their decisions, especially relevant in human-centric fields. We im ...

2022

Time-Frequency Characterization of Resting-State Brain Function Reveals Overlapping Components with Specific Topology and Frequency Content

Dimitri Nestor Alice Van De Ville, Thomas William Arthur Bolton

Even at rest, functional magnetic resonance imaging (fMRI) data displays exquisitely complex temporal dynamics. Here, we deployed a time-frequency analysis to track the modulus of fMRI signals over time, across space (a set of 341 brain areas) and frequenc ...

ASSOC COMPUTING MACHINERY2019

Global Sensitivity Analysis of Transient Code Output Applied to a Reflood Experiment Model using the TRACE Code

Andreas Pautz, Damar Canggih Wicaksono, Omar Zerkak

Appropriate model assessment requires proper understanding of the impact of variations of model parameters and their interactions on results. However, in many thermal-hydraulic (TH) simulations, the code often predicts time-dependent output where the impac ...

American Nuclear Society2016

Total Variation Regularization for Manifold-Valued Data

Martin Kurt Storath

We consider total variation (TV) minimization for manifold-valued data. We propose a cyclic proximal point algorithm and a parallel proximal point algorithm to minimize TV functionals with l(p) -type data terms in the manifold case. These algorithms are ba ...

Siam Publications2014

Gait disturbances as specific predictive markers of the first fall onset in elderly people: a two-year prospective observational study

Jean-Baptiste Mignardot

Falls are common in the elderly, and potentially result in injury and disability. Thus, preventing falls as soon as possible in older adults is a public health priority, yet there is no specific marker that is predictive of the first fall onset. We hypothe ...

Frontiers Research Foundation2014

Beltrami-Flow to Generate a Scale-Space of Cortical Feature Maps on the Sphere.

Jean-Philippe Thiran, Dominique Zosso

In this paper we define a scale-space for cortical mean curvature maps on the sphere, that offers a hierarchical representation of the cortical structures, useful in multi-scale algorithms. A spherical feature map is obtained through inflation of the corti ...

2009

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Explained variation

What drives electricity tariffs in Switzerland? Two-stage statistical and geospatial analysis of structural differences across 1913 municipalities

Characterization of high harmonic frequencies in reactor noise experiments within the CORTEX project

Evaluating the Explainers: Black-Box Explainable Machine Learning for Student Success Prediction in MOOCs

Time-Frequency Characterization of Resting-State Brain Function Reveals Overlapping Components with Specific Topology and Frequency Content

Stochastic Zeroth-Order Optimisation Algorithms with Variance Reduction

Global Sensitivity Analysis of Transient Code Output Applied to a Reflood Experiment Model using the TRACE Code

Sparsity-Based Data Reconstruction Models for Biomedical Imaging

Total Variation Regularization for Manifold-Valued Data

Gait disturbances as specific predictive markers of the first fall onset in elderly people: a two-year prospective observational study

Beltrami-Flow to Generate a Scale-Space of Cortical Feature Maps on the Sphere.

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Chat with Graph Search

Gait disturbances as specific predictive markers of the first fall onset in elderly people: a two-year prospective observational study

Sparsity-Based Data Reconstruction Models for Biomedical Imaging

Evaluating the Explainers: Black-Box Explainable Machine Learning for Student Success Prediction in MOOCs

Time-Frequency Characterization of Resting-State Brain Function Reveals Overlapping Components with Specific Topology and Frequency Content

Characterization of high harmonic frequencies in reactor noise experiments within the CORTEX project

Stochastic Zeroth-Order Optimisation Algorithms with Variance Reduction

Global Sensitivity Analysis of Transient Code Output Applied to a Reflood Experiment Model using the TRACE Code

Beltrami-Flow to Generate a Scale-Space of Cortical Feature Maps on the Sphere.

Total Variation Regularization for Manifold-Valued Data

What drives electricity tariffs in Switzerland? Two-stage statistical and geospatial analysis of structural differences across 1913 municipalities