Simulation based bayesian econometric inference: principles and some recent computational advances. [PDF]
In this paper we discuss several aspects of simulation basedBayesian econometric inference. We start at an elementary level on basic concepts of Bayesian analysis; evaluatingintegrals by simulation methods is a crucial ingredientin Bayesian inference ...
Dijk, H.K. van +2 more
core +1 more source
Unveiling Localized Heat in Lithium‐Ion Cells for Intelligent Temperature Sensing
Advanced Energy and Sustainability Research, EarlyView.Heat generation, thermal responses, and intelligent management in batteries. Lithium‐ion batteries (LIBs) power electric vehicles, portable electronics, and grid‐scale storage, yet their safety, performance, and lifetime are constrained by thermal effects.
Yunke Wang +6 more
wiley +1 more source
Modelling daily plant growth response to environmental conditions in Chinese solar greenhouse using Bayesian neural network. [PDF]
Sci Rep, 2023 Mohmed G +6 more
europepmc +1 more source
A multiscale Bayesian optimization framework for process and material codesign
AIChE Journal, EarlyView.Abstract The simultaneous design of processes and enabling materials such as solvents, catalysts, and adsorbents is challenging because molecular‐ and process‐level decisions are strongly interdependent. Sequential approaches often yield suboptimal results since improvements in material properties may not translate into superior process performance. We
Michael Baldea
wiley +1 more source
EpICC: A Bayesian neural network model with uncertainty correction for a more accurate classification of cancer. [PDF]
Sci Rep, 2022 Joshi P, Dhar R.
europepmc +1 more source
Advanced Intelligent Discovery, EarlyView.Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley +1 more source
A Bayesian neural network predicts the dissolution of compact planetary systems. [PDF]
Proc Natl Acad Sci U S A, 2021 Cranmer M +7 more
europepmc +1 more source
Advanced Intelligent Discovery, EarlyView.A sequential deep learning framework is developed to model surface roughness progression in multi‐stage microneedle fabrication. Using real‐world experimental data from 3D printing, molding, and casting stages, an long short‐term memory‐based recurrent neural network captures the cumulative influence of geometric parameters and intermediate outputs ...
Abdollah Ahmadpour +5 more
wiley +1 more source
Hyperparameter Optimization of Bayesian Neural Network Using Bayesian Optimization and Intelligent Feature Engineering for Load Forecasting. [PDF]
Sensors (Basel), 2022 Zulfiqar M +3 more
europepmc +1 more source