Results 231 to 240 of about 471,788 (278)

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

ParamNet: A Physics‐Guided Deep Learning Framework for Intelligent Self‐Inversion of Vacuum Optical Levitation Systems

Advanced Intelligent Systems, EarlyView.
A physics‐guided deep learning framework, ParamNet, is introduced for the intelligent self‐inversion of vacuum optical tweezers. By fuzing dual‐branch time–frequency features with physical dynamical constraints, it achieves high‐accuracy calibration of trap parameters from short‐window, low‐frequency trajectories, outperforming traditional methods ...
Qi Zheng, Wenfeng Fan, Feng Li, Jian Wu, Wei Quan   +4 more
wiley   +1 more source

Accelerated Discovery‐to‐Unveiling of High‐Performance and Affordable Ammonia Electrode Process by Human–Machine Collaboration Framework

Angewandte Chemie, EarlyView.
By employing dimensionally reduced reaction descriptors, a human–machine collaboration framework for efficient electrochemical nitrate reduction to NH3 electrocatalysts screening is established and drastically shorten the discovery timeframe. A new kinetic model is established in combination with a rotating ring‐disk electrode, unveiling the pivotal ...
Yingying Cheng, Masaki Takeguchi, Abraham Castro Garcia, Ken Sakaushi   +3 more
wiley   +2 more sources

Choice experiments on land managers' participation in environmental programs: A systematic review and meta‐analysis of estimate validity

American Journal of Agricultural Economics, EarlyView.
Abstract Discrete choice experiments are increasingly being used to estimate land managers' willingness to accept participation in incentive‐based environmental programs. This is a specific application of discrete choice experiments: the estimation of willingness to accept for a private good (program participation) where respondents have to make trade ...
Anastasio J. Villanueva, Angel Perni, Jesus Barreiro‐Hurle   +2 more
wiley   +1 more source

Automated Dynamic Flow Experimentation for Rapid Kinetic Fitting of Transition Metal Catalysis

Angewandte Chemie, EarlyView.
We have developed an automated dynamic flow experimentation platform to automatically fit and identify the most accurate kinetic model from a generated set of candidates. Three transition metal‐catalyzed transformations were performed using this workflow.
Florian L. Wagner, Klara Silber, Tobias A. Doliner, C. Oliver Kappe   +3 more
wiley   +2 more sources

A Global Prospective Harmonization Framework for Suicidality, Anhedonia, and Obsessive‐Compulsive Symptoms in Psychiatric Genetic Studies: A Cross‐Continental Study Within the Ancestral Population Network

American Journal of Medical Genetics Part B: Neuropsychiatric Genetics, EarlyView.
ABSTRACT This study aims to prospectively collect harmonized, quantitative, and dimensional psychiatric phenotypes (suicidality, anhedonia, and obsessive‐compulsive symptoms) and information on discrimination, stigma, and unfair treatment in up to 27,500 individuals across diverse ancestries and clinical populations for genetic analysis within the NIMH
Ana M. Diaz‐Zuluaga, Jacey L. Anderberg, Ana M. Ramirez‐Diaz, Andrea Horvath Marques, Catherine E. Rast, Daniel Bustamante, Deborah Jonker, Johanna Valencia‐Echeverry, Joseph Kyebuzibwa, Josselyn S. Muñoz, Kristien van der Walt, Mauricio Castaño Ramirez, Olivia Wootton, Renee M. Frederick, Rocky E. Stroud II, Ruben Gur, Sang Jin Rhee, Shaili C. Jha, Stella Gichuru, Susan Service, Victor I. Reus, Akena Dickens, Carlos Lopez‐Jaramillo, Carrie E. Bearden, Dan J. Stein, Ezra S. Susser, James J. Crowley, Jonathan Flint, Kenneth S. Kendler, Lukoye Atwoli, Michele T. Pato, Nelson B. Freimer, Roel A. Ophoff, Yong Min Ahn, Loes Olde Loohuis, Eric A. Storch, Bizu Gelaye   +36 more
wiley   +1 more source

Multi‐Objective Catalyst Discovery in High‐Entropy Alloy Composition Space: The Role of Noble Metals on the Pareto Front for Oxygen Reduction Reaction

Angewandte Chemie, EarlyView.
Pareto optimal compositions of alloy catalyst for oxygen reduction reaction are uncovered through multi‐objective Bayesian optimization of activity, stability, and material cost in an eight‐element high‐entropy alloy composition space. The substantial Pareto front obtained is compared to experimental literature and analyzed to elucidate the roles and ...
Mads K. Plenge, Ahmad Tirmidzi, Christian M. Clausen, Matthias Arenz, Jan Rossmeisl   +4 more
wiley   +1 more source

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Bayesian learning

SSRN Electronic Journal, 2021
We survey work using Bayesian learning in macroeconomics, highlighting common themes and new directions. First, we present many of the common types of learning problems agents face-signal extraction problems-and trace out their effects on macro aggregates, in different strategic settings.
Isaac Baley, Laura Veldkamp
openaire   +3 more sources