Results 61 to 70 of about 13,914 (280)

Dictionary‐based weak‐form training for noise‐robust series hybrid models with multiplicative unknowns

AIChE Journal, EarlyView.
ABSTRACT Hybrid modeling combines first‐principles equations with a data‐driven subcomponent. Training for the data‐driven part is sensitive to measurement noise when training targets are constructed using pointwise time derivatives. Beyond differentiation errors, hybrid models involve solving an inverse problem to estimate the data‐driven term, which ...
Hangjun Cho, Akshay Kudva, Parth Shah, Dongheon Lee, Joseph Sang‐Il Kwon   +4 more
wiley   +1 more source

Epistemic Trust, Mistrust and Credulity Questionnaire (ETMCQ) validation in French language: Exploring links to loneliness.

PLoS ONE
The concept of epistemic trust is gaining traction in the mental health field. Epistemic trust is thought to play a foundational role as a resilience factor against the development and maintenance of psychopathology by fostering social learning.
Christian Greiner, Vincent Besch, Marissa Bouchard-Boivin, Catherine Le Hénaff, Cécilia Von Rohr-De Pree, Nader Perroud, Paco Prada, Martin Debbané   +7 more
doaj   +1 more source

The Emergence of Epistemic Communities in the 'Sphaera' Corpus: Mechanisms of Knowledge Evolution

Journal of Historical Network Research, 2019
The present work investigates the process of emergence of new epistemic communities. The research is based on semantic, content-related data extracted from a corpus of 359 printed editions, mainly of textbooks used to teach cosmology at European ...
Matteo Valleriani, Florian Kräutli, Maryam Zamani, Alejandro Tejedor, Christoph Sander, Malte Vogl, Sabine Bertram, Gesa Funke, Holger Kantz   +8 more
doaj   +1 more source

Multimodal Learning with Rashomon Analysis for Battery Discharge Capacity Prediction

Advanced Intelligent Discovery, EarlyView.
Multimodal fusion integrates composition, crystal‐structure, and radial‐distribution descriptors to predict battery discharge capacity. Rashomon analysis across near‐optimal models reveals that explanatory variation is structured rather than arbitrary, separating stable mechanistic signals from model‐contingent attributions and providing a more ...
Jue Gong, Lejia Wang, Tianqing Zhu, Keith Butler, Sichao Li   +4 more
wiley   +1 more source

Artificial Intelligence‐Driven Network Pharmacology: A Methodological Paradigm Shift Bridging Traditional Wisdom and Modern Science

Advanced Intelligent Discovery, EarlyView.
Artificial intelligence is redefining network pharmacology (NP). By integrating knowledge graph engineering, geometric deep learning, multiomics anchoring, and generative reasoning, AI‐driven NP (AI‐NP) transforms static target mapping into dynamic, predictive modeling.
Cong Wang, Sile Hu, Rigahai Ji, Riguna A, Siqige Hao, Ma Zhuo, Yi‐Hung Chen, Bisihalatu Hu, Ulana Bai, Xigui Hada   +9 more
wiley   +1 more source

Predicting Performance of Hall Effect Ion Source Using Machine Learning

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
This study introduces HallNN, a machine learning tool for predicting Hall effect ion source performance using a neural network ensemble trained on data generated from numerical simulations. HallNN provides faster and more accurate predictions than numerical methods and traditional scaling laws, making it valuable for designing and optimizing Hall ...
Jaehong Park, Guentae Doh, Dongho Lee, Youngho Kim, Changmin Shin, Su‐Jin Shin, Young‐Chul Ghim, Sanghoo Park, Wonho Choe   +8 more
wiley   +1 more source

Beyond paradigms in Organization Studies: the Circle of Epistemic Matrices

Cadernos EBAPE.BR
In this article, I present a sketch of a new proposition to guide organizational studies: the Cicle of Epistemic Matrices. Inspired by Thomas Kuhn and based on the thesis of paradigms' incommensurability, Gibson Burrell and Gareth Morgan drew the diagram
Ana Paula Paes de Paula
doaj   +1 more source

Disentangling Aleatoric and Epistemic Uncertainty in Physics‐Informed Neural Networks: Application to Insulation Material Degradation Prognostics

Advanced Intelligent Systems, EarlyView.
Physics‐Informed Neural Networks (PINNs) provide a framework for integrating physical laws with data. However, their application to Prognostics and Health Management (PHM) remains constrained by the limited uncertainty quantification (UQ) capabilities.
Ibai Ramirez, Jokin Alcibar, Joel Pino, Mikel Sanz, Jose I. Aizpurua   +4 more
wiley   +1 more source

Dimensions of the AI Divide: Digital Inequality and Psychological Consequences

AI &Innovation, EarlyView.
ABSTRACT Artificial intelligence (AI) has become a foundational component of contemporary social, economic, and political life. Yet, the ways in which AI reshapes patterns of exclusion beyond questions of access and technical capability remain insufficiently theorized.
Christos Papaioannou
wiley   +1 more source

Innovative Artificial Intelligence‐Assisted Systems for Social Science Research: Architecture Design and Applied Practice

AI &Innovation, EarlyView.
ABSTRACT The rapid advancement of large language model (LLM) technology is profoundly transforming the practice of social science research. Scholarly discussions on Artificial Intelligence (AI)'s role in social science research can be organised into three levels: AI as a research tool, AI as a methodological infrastructure and AI as a quasi‐cognitive ...
Jie Xiong
wiley   +1 more source