Results 171 to 180 of about 3,084 (253)

Three shades of self‐regulation with unique complex dynamics, drivers and targets for intervention

open access: yesBritish Journal of Educational Technology, EarlyView.
Abstract Self‐regulated learning (SRL) is an active process involving multiple interacting components that evolve over time, exhibiting characteristics of complex systems such as non‐linearity, emergent behaviour, self‐organization, and hierarchy. These interactions unfold at different temporal levels, each warranting a dedicated lens to capture their ...
Sonsoles López‐Pernas   +2 more
wiley   +1 more source

Using multilabel classification neural network to detect intersectional DIF with small sample sizes

open access: yesBritish Journal of Mathematical and Statistical Psychology, EarlyView.
Abstract This study introduces InterDIFNet, a multilabel classification neural network for detecting intersectional differential item functioning (DIF) in educational and psychological assessments, with a focus on small sample sizes. Unlike traditional marginal DIF methods, which often fail to capture the effects of intersecting identities and require ...
Yale Quan, Chun Wang
wiley   +1 more source

Regularized reduced rank regression for mixed predictor and response variables

open access: yesBritish 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
wiley   +1 more source

Hierarchical Differentiable Fluid Simulation

open access: yesComputer Graphics Forum, EarlyView.
We introduce a two‐step algorithm that significantly reduces memory usage for solving control problems using differentiable fluid simulation techniques: our method first optimizes for bulk forces at reduced resolution, then refines local details over sub‐domains while maintaining differentiability. In trading runtime for memory, it enables optimization
Xiangyu Kong   +4 more
wiley   +1 more source

SDFs from Unoriented Point Clouds using Neural Variational Heat Distances

open access: yesComputer 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

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