Results 91 to 100 of about 207 (176)
LLpowershap: logistic loss-based automated Shapley values feature selection method. [PDF]
BMC Med Res MethodolMadakkatel I, Hyppönen E.
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Regularized reduced rank regression for mixed predictor and response variables
British Journal of Mathematical and Statistical Psychology, EarlyView.Abstract In this paper, we introduce the Generalized Mixed Regularized Reduced Rank Regression model (GMR4), an extension of the GMR3 model designed to improve performance in high‐dimensional settings. GMR3 is a regression method for a mix of numeric, binary and ordinal response variables, while also allowing for mixed‐type predictors through optimal ...
Lorenza Cotugno +2 more
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"In Mathematical Language": On Mathematical Foundations of Quantum Foundations. [PDF]
Entropy (Basel)Plotnitsky A.
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Bio-Inspired Genetic Algorithms with Formalized Crossover Operators for Robotic Applications. [PDF]
Front Neurorobot, 2017 Zhang J, Kang M, Li X, Liu GY.
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British Journal of Mathematical and Statistical Psychology, EarlyView.Abstract Standardized mean differences (SMDs) are widely used to quantify treatment effects in cluster‐randomized trials. However, covariate adjustment in hierarchical linear models reduces the residual variance components used for standardization, which artificially inflates effect size estimates and undermines comparability across studies. We propose
Juyoung Jung +2 more
wiley +1 more source
Geometric standardized mean difference and its application to meta‐analysis
British Journal of Mathematical and Statistical Psychology, EarlyView.Abstract The standardized mean difference (SMD) is a widely used measure of effect size, particularly common in psychology, clinical trials and meta‐analysis involving continuous outcomes. Traditionally, under the equal variance assumption, the SMD is defined as the mean difference divided by a common standard deviation.
Jiandong Shi +4 more
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SDFs from Unoriented Point Clouds using Neural Variational Heat Distances
Computer Graphics Forum, EarlyView.We propose a novel variational approach for computing neural Signed Distance Fields (SDF) from unoriented point clouds. We first compute a small time step of heat flow (middle) and then use its gradient directions to solve for a neural SDF (right). Abstract We propose a novel variational approach for computing neural Signed Distance Fields (SDF) from ...
Samuel Weidemaier +5 more
wiley +1 more source
TABI: Tight and Balanced Interactive Atlas Packing
Computer Graphics Forum, EarlyView.Abstract Atlas packing is a key step in many computer graphics applications. Packing algorithms seek to arrange a set of charts within a fixed‐size atlas with as little downscaling as possible. Many packing applications such as content creation tools, dynamic atlas generation for video games, and texture space shading require on‐the‐fly interactive ...
F. Gu, N. Vining, A. Sheffer
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A Verified SAT Solver Framework with Learn, Forget, Restart, and Incrementality. [PDF]
J Autom Reason, 2018 Blanchette JC +3 more
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Volume Quantization with Flexible Singularities for Hexahedral Meshing
Computer Graphics Forum, EarlyView.Abstract We present a novel algorithm for quantization and subsequent hexahedral mesh generation from seamless volumetric maps. Quantization is the process of choosing integers that represent the numbers of hexahedral elements to be placed in each region of the volume, and transforming the seamless map into an integer‐grid map matching that choice ...
H. Brückler, M. Campen
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