Results 121 to 130 of about 302 (183)

Compact and Interpretable Neural Networks Using Lehmer Activation Units. [PDF]

Entropy (Basel)
Ataei M, Forouzi S, Wang X.
europepmc   +1 more source

Color and gloss constancy under diverse lighting environments. [PDF]

J Vis, 2023
Morimoto T, Akbarinia A, Storrs K, Cheeseman JR, Smithson HE, Gegenfurtner KR, Fleming RW.   +6 more
europepmc   +1 more source

Beyond Traditional Covariates: An Interpretable Machine Learning Workflow for Improved Hybrid Pharmacometric Modeling

CPT: Pharmacometrics &Systems Pharmacology, Volume 15, Issue 8, August 2026.
ABSTRACT Model‐informed precision dosing is often constrained by the limited generalizability of traditional population pharmacokinetic models, especially in critically ill patients. A hybrid machine learning‐population pharmacokinetic framework is proposed to improve a priori pharmacokinetic predictions by integrating real‐world clinical data.
Freek J. A. Relouw, Jort J. M. T. Lokers, Tim Preijers, Sebastiaan D. T. Sassen, Natal A. W. van Riel, Birgit C. P. Koch   +5 more
wiley   +1 more source

Scalable Approximation of the Transformation‐Free Linear Simplicial–Simplicial Regression via Constrained Iterative Reweighted Least Squares

Statistical Analysis and Data Mining: An ASA Data Science Journal, Volume 19, Issue 4, August 2026.
ABSTRACT Simplicial–simplicial regression concerns statistical modeling scenarios in which both the predictors and the responses contain vectors constrained to lie on the simplex. Fiksel et al. introduced a transformation‐free linear regression framework for this setting, wherein the regression coefficients are estimated by minimizing the Kullback ...
Michail Tsagris, Omar Alzeley
wiley   +1 more source

<i>CURATE</i>: Scaling-Up Differentially Private Causal Graph Discovery. [PDF]

Entropy (Basel)
Bhattacharjee P, Tandon R.
europepmc   +1 more source

A Next‐Generation Snow Albedo Parameterization for Climate Modeling Using Constrained Machine Learning

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 4, August 2026.
Abstract We demonstrate a data‐driven parameterization framework for snow albedo evolution using a constrained auto‐regressive neural differential equation that directly predicts snow albedo change from standard meteorological inputs. After training with multi‐year in situ and satellite observations from a wide variety of locations, the scheme ...
A. Charbonneau, K. Deck, T. Schneider
wiley   +1 more source

TMPA-HC: a two-stage heterogeneous multi-population algorithm with cooperative search for high-dimensional feature selection. [PDF]

Sci Rep
Chen A, Pan P, Quan N, Zhou B.
europepmc   +1 more source

Colors and Things. [PDF]

Iperception, 2020
Koenderink J, van Doorn A, Gegenfurtner K.   +2 more
europepmc   +1 more source

Simplex‐based model for nanoparticle grain identification in four‐dimensional scanning transmission electron microscopy data

Journal of Microscopy, Volume 303, Issue 2, Page 194-215, August 2026.
Abstract Grain identification in polycrystalline nanoparticles, for example, determining which crystal phases are present at each spatial location, is fundamental to materials characterisation. This is particularly challenging when grains overlap extensively, as commonly occurs in four‐dimensional scanning transmission electron microscopy (4D‐STEM ...
Wei Liu, Roberto dos Reis, Chad A. Mirkin, Vinayak P. Dravid, Wei Chen, Daniel W. Apley   +5 more
wiley   +1 more source

Modeling information demand in the framework of probabilistic reasoning. [PDF]

Commun Psychol
Jiwa MW, Gottlieb J.
europepmc   +1 more source