Results 101 to 110 of about 1,563,284 (329)
Statistical post-processing of hydrological forecasts using Bayesian model averaging [PDF]
, 2018 Accurate and reliable probabilistic forecasts of hydrological quantities like runoff or water level are beneficial to various areas of society. Probabilistic state-of-the-art hydrological ensemble prediction models are usually driven with meteorological ...
Ayari, Mehrez El +2 more
core +2 more sources
Generative Models for Crystalline Materials
Advanced Materials, EarlyView.Generative machine learning models are increasingly used in crystalline materials design. This review outlines major generative approaches and assesses their strengths and limitations. It also examines how generative models can be adapted to practical applications, discusses key experimental considerations for evaluating generated structures, and ...
Houssam Metni +15 more
wiley +1 more source
Entropy, 2013 Studies of learning algorithms typically concentrate on situations where potentially ever growing training sample is available. Yet, there can be situations (e.g., detection of differentially expressed genes on unreplicated data or estimation of time ...
Peter Tiňo
doaj +1 more source
Comparative Risk Assessment for Fossil Energy Chains Using Bayesian Model Averaging
Energies, 2020 The accident risk of severe (≥5 fatalities) accidents in fossil energy chains (Coal, Oil and Natural Gas) is analyzed. The full chain risk is assessed for Organization for Economic Co-operation and Development (OECD), 28 Member States of the ...
Matteo Spada, Peter Burgherr
doaj +1 more source
On the Choice of Prior in Bayesian Model Averaging [PDF]
Bayesian model averaging attempts to combine parameter estimation and model uncertainty in one coherent framework. The choice of prior is then critical.
Einmahl, J.H.J., Kumar, K., Magnus, J.R.
core +1 more source
Instrumental Variable Bayesian Model Averaging via Conditional Bayes Factors [PDF]
, 2012 We develop a method to perform model averaging in two-stage linear regression systems subject to endogeneity. Our method extends an existing Gibbs sampler for instrumental variables to incorporate a component of model uncertainty.
Karl, Anna, Lenkoski, Alex
core
Oxygen Evolution Reaction Catalysts for Acidic‐Media CO2 Electrolyzers
Advanced Materials, EarlyView.Acidic‐media CO2 electroreduction (CO2R) could decarbonize chemical production, despite relying on rare‐earth elements for anodic oxygen evolution reaction (OER). Transferring the learnings from mature sister technologies (water electrolysis) could accelerate technological development.
Mingcheng Huang, Adnan Ozden
wiley +1 more source
Probabilistic Precipitation Forecasting over East Asia Using Bayesian Model Averaging
Weather and forecasting, 2019 Bayesian model averaging (BMA) was applied to improve the prediction skill of 1–15-day, 24-h accumulated precipitation over East Asia based on the ensemble prediction system (EPS) outputs of ECMWF, NCEP, and UKMO from the TIGGE datasets.
Luying Ji +3 more
semanticscholar +1 more source
Hard‐Magnetic Soft Millirobots in Underactuated Systems
Advanced Robotics Research, EarlyView.This review provides a comprehensive overview of hard‐magnetic soft millirobots in underactuated systems. It examines key advances in structural design, physics‐informed modeling, and control strategies, while highlighting the interplay among these domains.
Qiong Wang +4 more
wiley +1 more source
BAYESIAN CURVE ESTIMATION BY MODEL AVERAGING [PDF]
A bayesian approach is used to estimate a nonparametric regression model. The main features of the procedure are, first, the functional form of the curve is approximated by a mixture of local polynomials by Bayesian Model Averaging (BMA); second, the ...
Daniel Peña, M. Dolores Redondas
core