Results 51 to 60 of about 149,758 (276)
A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions
This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice +2 more
wiley +1 more source
Automatic Variational Inference in Stan [PDF]
Variational inference is a scalable technique for approximate Bayesian inference. Deriving variational inference algorithms requires tedious model-specific calculations; this makes it difficult to automate.
Blei, David M. +3 more
core
Accelerated Parallel Non-conjugate Sampling for Bayesian Non-parametric Models
Inference of latent feature models in the Bayesian nonparametric setting is generally difficult, especially in high dimensional settings, because it usually requires proposing features from some prior distribution. In special cases, where the integration
Perez-Cruz, Fernando +2 more
core +1 more source
Multimodal Data‐Driven Microstructure Characterization
A self‐consistent autonomous workflow for EBSP‐based microstructure segmentation by integrating PCA, GMM clustering, and cNMF with information‐theoretic parameter selection, requiring no user input. An optimal ROI size related to characteristic grain size is identified.
Qi Zhang +4 more
wiley +1 more source
We present a fully automated Bayesian optimization (BO) protocol for the parameterization of nonbonded interactions in coarse‐grain CG force fields (BACH). Using experimental thermophysical data, we apply the protocol to a broad range of liquids, spanning linear, branched, and unsaturated hydrocarbons, esters, triglycerides, and water.
Janak Prabhu +3 more
wiley +1 more source
Recursive Noise Adaptive Extended Object Tracking by Variational Bayesian Approximation
This paper proposes an adaptive extended object tracking algorithm with unknown time-varying sensor error covariance in linear state-space models. The proposed algorithm employs Inverse Wishart distribution to describe the full covariance.
Zhifei Li +3 more
doaj +1 more source
Approximate Bayesian Inference for Doubly Robust Estimation
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Graham, Daniel J. +2 more
openaire +4 more sources
Superionic Amorphous Li2ZrCl6 and Li2HfCl6
Amorphous Li2HfCl6 and L2ZrCl6 are shown to be promising solid‐state electrolytes with predicted ionic conductivities >20 mS·cm−1. Molecular dynamics simulations with machine‐learning force fields reveal that anion vibrations and flexible MCl6 octahedra soften the Li coordination cage and enhance mobility. Correlation between Li‐ion diffusivity and the
Shukai Yao, De‐en Jiang
wiley +1 more source
Consensus Formation and Change are Enhanced by Neutrality
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
Hierarchical Summary Statistics Encoding Across Primary Visual and Posterior Parietal Cortices
This study shows that mouse V1 simultaneously encodes the ensemble mean and variance of motion, providing a robust summary‐statistic representation that persists despite single‐neuron variability. These signals propagate to PPC, where they are transformed into abstract category representations during decision making.
Young‐Beom Lee +4 more
wiley +1 more source

