Results 111 to 120 of about 1,871,243 (292)
Probability in the Everett World: Comments on Wallace and Greaves [PDF]
, 2006 It is often objected that the Everett interpretation of QM cannot make sense of quantum probabilities, in one or both of two ways: either it can’t make sense of probability at all, or it can’t explain why probability should be governed by the Born rule ...
Price, Huw
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Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion
Advanced Intelligent Discovery, EarlyView.This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia +1 more
wiley +1 more source
Advanced Intelligent Discovery, EarlyView.This article implements a unified human digital twin framework that integrates cutting edge actuation, sensing, simulation, and bidirectional feedback capability. The approach includes integrating multimodal sensing, AI, and biomechanical simulation into one compact system.
Tajbeed Ahmed Chowdhury +4 more
wiley +1 more source
The psychology of Bayesian reasoning
Frontiers in Psychology, 2014 David R. Mandel
doaj +1 more source
Nonresponse and Focal Point Answers to Subjective Probability Questions [PDF]
We develop and estimate a panel data model explaining the answers to questions about subjective probabilities, using data from the US Health and Retirement Study. We explicitly account for nonresponse, rounding, and focal point “50 percent” answers.
Kleinjans, Kristin J., van Soest, Arthur
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Advanced Intelligent Discovery, EarlyView.The authors develop a deep learning model for real‐time tracking of wound progression. The deep learning framework maps the nonlinear evolution of a time series of images to a latent space, where they learn a linear representation of the dynamics. The linear model is interpretable and suitable for applications in feedback control.
Fan Lu +11 more
wiley +1 more source
The Myth of Judicial Objectivity: Why Subjectivity is The Only Path to a Transparent Trial
Quaestio FactiThis comment addresses the ‘prior challenge’ in forensic Bayesian modelling, recently highlighted by Anne Ruth Mackor (2026). We argue that the perceived lack of frequency data is not an insurmountable obstacle but a misconception rooted in an outdated ...
Silvia Bozza +2 more
doaj +1 more source
Machine‐Learning‐Assisted Onset‐Time Determination in Transient Luminescence Thermometry
Advanced Intelligent Discovery, EarlyView.Artificial neural networks enable autonomous extraction of onset times from transient heating curves in luminescence thermometry. Using Ln3+‐doped upconverting nanoparticles as luminescent thermometers, we combine experimental transients with physically motivated synthetic curves to enhance data diversity and improve generalization.
David J. Sousa +3 more
wiley +1 more source
Advanced Intelligent Discovery, EarlyView.Machine learning serves as a central engine for the intelligent characterization of two‐dimensional materials by integrating multimodal techniques, including optical microscopy, spectroscopy, electron microscopy, and scanning probe microscopy (SPM). This unified framework enables automated, high‐throughput, and quantitative extraction of structural ...
Zhi‐Long Cao, Jia‐Xu Yan
wiley +1 more source
Relationship between Future Time Orientation and Item Nonresponse on Subjective Probability Questions: A Cross-Cultural Analysis. [PDF]
J Cross Cult Psychol, 2017 Lee S, Liu M, Hu M.
europepmc +1 more source