Diagnosis of partially observed petri net based on analytical redundancy relationships
Sign Up to like & getrecommendations! Published in 2019 at "Asian Journal of Control"
DOI: 10.1002/asjc.1832
Abstract: In this paper, we design an efficient diagnosis technique for partially observed discrete event systems modeled by labeled Petri nets. The fault detection is based on analytical redundancy relationships derived from the nominal model. The… read more here.
Keywords: diagnosis partially; analytical redundancy; based analytical; partially observed ... See more keywords
Hidden mover-stayer model for disease progression accounting for misclassified and partially observed diagnostic tests: Application to the natural history of human papillomavirus and cervical precancer.
Sign Up to like & getrecommendations! Published in 2021 at "Statistics in medicine"
DOI: 10.1002/sim.8977
Abstract: Hidden Markov models (HMMs) have been proposed to model the natural history of diseases while accounting for misclassification in state identification. We introduce a discrete time HMM for human papillomavirus (HPV) and cervical precancer/cancer where… read more here.
Keywords: cervical precancer; natural history; model; partially observed ... See more keywords
Optimization Based Methods for Partially Observed Chaotic Systems
Sign Up to like & getrecommendations! Published in 2019 at "Foundations of Computational Mathematics"
DOI: 10.1007/s10208-018-9388-x
Abstract: In this paper we consider filtering and smoothing of partially observed chaotic dynamical systems that are discretely observed, with an additive Gaussian noise in the observation. These models are found in a wide variety of… read more here.
Keywords: optimization based; based methods; methods partially; partially observed ... See more keywords
Importance sampling for partially observed temporal epidemic models
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DOI: 10.1007/s11222-018-9827-1
Abstract: We present an importance sampling algorithm that can produce realisations of Markovian epidemic models that exactly match observations, taken to be the number of a single event type over a period of time. The importance… read more here.
Keywords: importance; time; partially observed; importance sampling ... See more keywords
Statistical inference for the intensity in a partially observed jump diffusion
Sign Up to like & getrecommendations! Published in 2019 at "Journal of Mathematical Analysis and Applications"
DOI: 10.1016/j.jmaa.2018.10.026
Abstract: Abstract This article focuses on a partially observed linear diffusion with jumps described by a Poisson process. Precisely, we study an inferential problem for the intensity of the Poisson process by establishing a moderate deviation… read more here.
Keywords: statistical inference; inference intensity; intensity partially; diffusion ... See more keywords
Recognizing activities from partially observed streams using posterior regularized conditional random fields
Sign Up to like & getrecommendations! Published in 2017 at "Neurocomputing"
DOI: 10.1016/j.neucom.2017.05.004
Abstract: Abstract Recognizing activities from behavior data is important for comprehensively understanding human’s intents and interests. However, in most cases, the user behaviors are partially observed or recorded, which make it a big challenge to model… read more here.
Keywords: conditional random; random fields; posterior regularized; recognizing activities ... See more keywords
Learning Latent Dynamics for Partially-Observed Chaotic Systems
Sign Up to like & getrecommendations! Published in 2020 at "Chaos"
DOI: 10.1063/5.0019309
Abstract: This paper addresses the data-driven identification of latent representations of partially observed dynamical systems, i.e., dynamical systems for which some components are never observed, with an emphasis on forecasting applications and long-term asymptotic patterns. Whereas… read more here.
Keywords: dynamics partially; data driven; partially observed; learning latent ... See more keywords
Handling missing data in a composite outcome with partially observed components: simulation study based on clustered paediatric routine data
Sign Up to like & getrecommendations! Published in 2021 at "Journal of Applied Statistics"
DOI: 10.1080/02664763.2021.1895087
Abstract: Composite scores are useful in providing insights and trends about complex and multidimensional quality of care processes. However, missing data in subcomponents may hinder the overall reliability ... read more here.
Keywords: handling missing; composite outcome; partially observed; missing data ... See more keywords
Classification framework for partially observed dynamical systems.
Sign Up to like & getrecommendations! Published in 2017 at "Physical Review E"
DOI: 10.1103/physreve.95.043303
Abstract: We present a general framework for classifying partially observed dynamical systems based on the idea of learning in the model space. In contrast to the existing approaches using point estimates of model parameters to represent… read more here.
Keywords: classification; framework; observed dynamical; model ... See more keywords
Identifiability and Estimation of Partially Observed Influence Models
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Control Systems Letters"
DOI: 10.1109/lcsys.2022.3184958
Abstract: The influence model (IM) is a discrete-time stochastic model that captures the spatiotemporal dynamics of networked Markov chains. Partially-observed IM (POIM) is an IM in which the statuses for some sites are unobserved. Identifiability and… read more here.
Keywords: estimation partially; influence; estimation; identifiability estimation ... See more keywords
Partially Observed Markov Decision Processes: From Filtering to Controlled Sensing [Bookshelf]
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Control Systems"
DOI: 10.1109/mcs.2019.2913493
Abstract: Optimal decision making under uncertainty is of increasing importance in artificial intelligence, machine learning, signal processing, and control. Partially observed Markov decision processes (POMDPs) are a significant paradigm in real-world sequential decision making. The framework… read more here.
Keywords: markov decision; partially observed; observed markov; controlled sensing ... See more keywords