Results 121 to 130 of about 10,800,365 (307)
Advanced Intelligent Systems, EarlyView.A hybrid Reinforcement Learning–Explainable AI framework integrates SHAP and LIME explanations directly into a Deep Q‐Network inference loop for real‐time ICU decision support. Trained on 18 142 mechanically ventilated stays from the eICU database, the system attains 93.0% decision accuracy, 20% fewer errors than RL alone, and a 91% clinician trust ...
Jannatul Ferdaus Disha +2 more
wiley +1 more source
Exploiting Edge Semantics in Job Shop Scheduling Problem With Heterogeneous Graph Transformers
Advanced Intelligent Systems, EarlyView.A heterogeneous graph transformer (HGT) is introduced for reinforcement learning‐based job shop scheduling by explicitly distinguishing precedence and machine‐contention relations through edge‐type‐specific attention. The proposed framework learns richer scheduling representations, improves decision quality over homogeneous graph models, and highlights
Bulent Soykan, Fatih Kasimoglu
wiley +1 more source
Convergence of stochastic process with Markov switching [PDF]
Математичні Студії, 2012 It has been established sufficient conditions for the convergence of a multi-dimensional stochastic process in the case of dependence of the regression function on the environment, which is described by Markov switchings.
O. I. Kiykovska, Ya. M. Chabanyuk
doaj
Variability and singularity arising from a Piecewise-Deterministic Markov Process applied to model poor patient compliance in the multi-IV case. [PDF]
J Appl Stat, 2020 Fermín LJ, Lévy-Véhel J.
europepmc +1 more source
, 2001 Essay by Lucina Ward. "Shelf + self is a series of installations shown in Canberra, Brisbane, Sydney, Melbourne, Adelaide and Perth throughout 2001-2003 ...
Zeljko Markov
core
Accelerating Materials Discovery: A Review of Machine Learning in X‐Ray Absorption Spectroscopy
Advanced Intelligent Systems, EarlyView.This review systematically details how machine learning transforms X‐ray absorption spectroscopy (XAS) analysis. It covers advanced deep learning architectures for structure‐spectra mapping and inverse tasks, while discussing key challenges like the simulation‐to‐reality gap.
Melaku Lake Tegegne +5 more
wiley +1 more source
Bayesian inference for Hidden Markov Model [PDF]
Hidden Markov Models can be considered an extension of mixture models, allowing for dependent observations. In a hierarchical Bayesian framework, we show how Reversible Jump Markov Chain Monte Carlo techniques can be used to estimate the parameters of ...
Luisa Scaccia, Rosella Castellano
core
Bayesian nonparametric hidden Markov models with application to the analysis of copy-number-variation in mammalian genomes [PDF]
, 2009 We consider the development of Bayesian Nonparametric methods for product partition models such as Hidden Markov Models and change point models.
Yau, C. +3 more
core
American Journal of Agricultural Economics, EarlyView.Abstract Large‐scale land reforms constitute a substantial redistribution of wealth and reallocation of agricultural land, which is a major form of asset and production input in developing countries. While land redistribution (from the rich to the poor) remains a highly controversial issue, extensive evidence on its effect is limited.
Devashish Mitra +3 more
wiley +1 more source
ON SEMI-MARKOV PROCESSES [PDF]
Proceedings of the National Academy of Sciences, 1964 openaire +3 more sources