Results 61 to 70 of about 165,261 (262)
A Bayesian copula model for stochastic claims reserving [PDF]
We present a full Bayesian model for assessing the reserve requirement of multiline Non-Life insurance companies. Bayesian models for claims reserving allow to account for expert knowledge in the evaluation of Outstanding Loss Liabilities, allowing the ...
Luca Regis
core +2 more sources
Bayesian Nonparametric Estimation and Consistency of Mixed Multinomial Logit Choice Models [PDF]
This paper develops nonparametric estimation for discrete choice models based on the Mixed Multinomial Logit (MMNL) model. It has been shown that MMNL models encompass all discrete choice models derived under the assumption of random utility maximization,
Lancelot F. James +2 more
core
Advanced Materials, EarlyView.This review summarizes the principles and challenges of nonaqueous lithium‐oxygen batteries and recent advances in cathode catalysts, including carbon‐based materials, metals, oxides, sulfides, nitrides, carbides, and redox mediators. It highlights emerging design strategies and artificial intelligence‐driven approaches, emphasizing data‐assisted ...
Yuqing Yao +8 more
wiley +1 more source
Weaving Intelligence: Thermally Drawn Multimaterial Fibers Toward AI‐Enabled Smart Textiles
Advanced Materials, EarlyView.Thermally drawn multimaterial fibers are rapidly advancing as intelligent structural units for next‐generation smart textiles. Integrating multimaterial architectures with neuromorphic and spiking‐neural‐network principles enables fabrics that can sense, compute, and adapt autonomously.
Vuong Dinh Trung +9 more
wiley +1 more source
Bayesian analysis of DSGE models [PDF]
This paper reviews Bayesian methods that have been developed in recent years to estimate and evaluate dynamic stochastic general equilibrium (DSGE) models.
Sungbae An, Frank Schorfheide
core
Advanced Materials, EarlyView.We introduce a computational workflow that combines quantum chemical calculations and machine learning techniques to predict the catalytic performance of a wide range of catalysts in the nitrogen reduction reaction (NRR). The analysis of the trained models provides insights into the complex structure–activity relationship in experimental catalytic ...
Leonardo Di Ciano +5 more
wiley +1 more source
A particle filter for freeway traffic estimation [PDF]
, 2004 This paper considers the traffic flow estimation problem for the purposes of on-line traffic prediction, mode detection and ramp-metering control. The solution to the estimation problem is given within the Bayesian recursive framework. A particle filter (
Mihaylova, Lyudmila +7 more
core +1 more source
Advanced Materials Technologies, EarlyView.This study shows that a lightweight blackbox neural network provides a practical, cost‐effective solution for bidirectional process prediction in laser‐induced graphene (LIG) fabrication. Achieving high predictive performance with minimal overhead, the approach democratizes machine learning (ML) for resource‐limited environments.
Maxim Polomoshnov +3 more
wiley +1 more source
Parameter estimation for a discrete-response model with double rules of sample selection: A Bayesian approach [PDF]
We present a Bayesian sampling approach to parameter estimation in a discrete-response model with double rules of selectivity, where the dependent variables contain two layers of binary choices and one ordered response.
Brett A. Inder, Rong Zhang, Xibin Zhang
core
Objective Bayes estimation and hypothesis testing : the reference-intrinsic approach [PDF]
, 2005 Conventional frequentist solutions to point estimation and hypothesis testing typically need ad hoc modifications when dealing with non-regular models, and may prove to be misleading.
Juárez, Miguel A.
core