Results 111 to 120 of about 3,905,952 (289)
Wind Energy and Engineering ResearchThis paper demonstrates the Bayesian Neural Network-based Supervisory Control and Data Acquisition data for fault detection in Horizontal Axis Wind Turbines.
Gaurav Jyoti Gogoi +2 more
doaj +1 more source
Muscle Control of an Extra Robotic Digit
Advanced Robotics Research, EarlyView.This study compares muscle‐ and movement‐based control for operating a supernumerary robotic thumb. While movement control performs better in the proposed tasks, muscle‐based (EMG) control promotes broader motor learning. The results highlight the promise and challenges of using biosignals for human augmentation, offering new insights into intuitive ...
Julien Russ +7 more
wiley +1 more source
Consensus Formation and Change are Enhanced by Neutrality
Advanced Science, EarlyView.Neutral agents are shown to enhance both the formation and overturning of consensus in collective decision‐making. A general mathematical model and experiments with locusts and humans reveal that neutrality enables robust consensus via simple interactions and accelerates consensus change by reducing effective population size.
Andrei Sontag +3 more
wiley +1 more source
On the shape of posterior densities and credible sets in instrumental variable regression models with reduced rank: an application of flexible sampling methods using neural networks [PDF]
Likelihoods and posteriors of instrumental variable regression models with strongendogeneity and/or weak instruments may exhibit rather non-elliptical contours inthe parameter space.
Hoogerheide, L.F. +2 more
core
Learning Ensembles of Neural Networks by Means of a Bayesian Artificial Immune System
, 2015 In this paper, we apply an immune-inspired approach to design ensembles of heterogeneous neural networks for classification problems. Our proposal, called Bayesian artificial immune system, is an estimation of distribution algorithm that replaces the ...
Castro, Pablo A Dalbem +3 more
core +1 more source
Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials
Advanced Science, EarlyView.Traditional black‐box models for polymer mechanics rely solely on data and lack physical interpretability. This work presents a physics‐embedded neural network (PENN) that integrates constitutive equations into machine learning. The approach ensures reliable stress predictions, provides interpretable parameters, and enables performance‐driven, inverse ...
Siqi Zhan +8 more
wiley +1 more source
Cox proportional hazards model with Bayesian neural network for survival prediction
Scientific ReportsSurvival analysis plays a crucial aspect in medical research and other domains where understanding the time-to-events is paramount. In this study, we present a novel approach for estimating survival outcomes that combines Bayesian neural networks with ...
Fojan Faghiri, Akram Kohansal
doaj +1 more source
, 2020 ## This item has been replaced by the one which can be found at https://datashare.ed.ac.uk/handle/10283/3886 ## This dataset contains the synthetic data and codes used to generate those data for manuscript "Bayesian geophysical inversion using ...
core +1 more source
ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals
Advanced Science, EarlyView.The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray +3 more
wiley +1 more source
An application of formal concept analysis to neural decoding [PDF]
, 2012 This paper proposes a novel application of Formal Concept Analysis (FCA) to neural decoding: the semantic relationships between the neural representations of large sets of stimuli are explored using concept lattices.
Priss, U, Endres, D M, Foldiak, Peter
core +2 more sources