Results 91 to 100 of about 436,673 (317)
, 1966 Bayes' original paper "Essay Towards Solving a Problem in the Doctrine of Change" was published in Philosophical Transactions of the Royal Society, 1763. Over 200 years, Bayes' Concepts have survived numerous critical onslaughts. Even though Bayesian Inference is still regarded as being somewhat unorthodox, it is becoming more generally accepted each ...
openaire +2 more sources
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
A Bayesian Hyperparameter Inference for Radon-Transformed Image Reconstruction
International Journal of Biomedical Imaging, 2011 We develop a hyperparameter inference method for image reconstruction from Radon transform which often appears in the computed tomography, in the manner of Bayesian inference.
Hayaru Shouno +2 more
doaj +1 more source
Bayesian Factor Analysis for Inference on Interactions [PDF]
, 2020 Federico Ferrari, David B. Dunson
openalex +1 more source
Advanced Science, EarlyView.This review examines the evolution of bioprinting toward minimally invasive in situ strategies for internal organ regeneration. It defines the technological roadmap from handheld systems to advanced minimally invasive bioprinting platforms, positioning soft robotics as a core enabler.
Duc Tu Vu +9 more
wiley +1 more source
Practical bounds on the error of Bayesian posterior approximations: A nonasymptotic approach
, 2018 Bayesian inference typically requires the computation of an approximation to the posterior distribution. An important requirement for an approximate Bayesian inference algorithm is to output high-accuracy posterior mean and uncertainty estimates ...
Broderick, Tamara +3 more
core
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
Bayesian Nonparametric Hidden Semi-Markov Models
, 2012 There is much interest in the Hierarchical Dirichlet Process Hidden Markov Model (HDP-HMM) as a natural Bayesian nonparametric extension of the ubiquitous Hidden Markov Model for learning from sequential and time-series data.
Johnson, Matthew J., Willsky, Alan S.
core
Multi‐Physical Field Modulated P‐Bit Device Based on VO2 Thin Film
Advanced Science, EarlyView.We have proposed a VO2‐based P‐bit device where synergistic multi‐physical field modulation enables real‐time tunability of randomness. Besides introducing a new phase‐change material‐based device approach for high‐performance P‐bits, this study also demonstrates a synergistic multi‐physical field modulation strategy that opens new opportunities for ...
Bowen Sun +10 more
wiley +1 more source