The DOI matches its Crossref record.
Markov Chains: From Theory to Implementation and Experimentation
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Integrity signals
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Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“In addition, the Markov model [159, 296] (elaborated 50 years earlier) was leveraged to construct a process based on discrete-time state transitions and action rewards, named Markov Decision Process (MDP), which formalizes sequential decision-making problems in a fully observable, controlled environment [46].”
From A comprehensive survey on machine learning for networking: Evolution, applications and research opportunities (2018) · cites this paper as [159]
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Items 401–413 of 413
From rarity to typicality : the improbable journey of a large deviation
Chabane, L. (2021) · theses.fr (ABES) · doi:10.70675/5829a6bezae11z454aza1d2z3618fbe4d26a · Cited by 14
Watermarking machine learning models
Lounici, S. (2022) · theses.fr (ABES) · doi:10.70675/2182b7a8zb67dz4845z9cb4z0f38acf7b0d1
Deep Learning Based Multimodal Retrieval
Chen, J. (2023) · theses.fr (ABES) · doi:10.70675/40665356z7b38z4e8fz8dceze1c899d3ae06
Macedo, L. T., Ferrari, V. E., Costa, E. F. D., Lourenço, G. J., Calonga, L., Castilho, A. M., Chone, C. T., & Lima, C. S. P. (2026) · PLoS ONE · doi:10.1371/journal.pone.0345371
Beyond Heuristics: A Predictive Modeling Framework for Multi-touch Attribution in Online Marketing
Krastevich, T. (2026) · Springer proceedings in business and economics · doi:10.1007/978-3-032-19276-9_25
Hossain, M. I., Biswas, S., & Mondal, M. S. (2026) · Discover Geoscience · doi:10.1007/s44288-026-00560-z
“The model is now widely used and proves effective for simulating urban growth and modeling the state of a system that changes with time [6, 15, 31, 41].”
Markov reads Puškin, again: A statistical journey into the poetic world of Evgenij Onegin
Sabatini, A. M. (2026) · PLoS ONE · doi:10.1371/journal.pone.0350827
“MD should be understood as a descriptive index summarizing the extent to which higher-order conditioning improves local predictability in a finite-order Markov representation [27].”
Benchmarking Hybrid Deep Learning Architectures for Predictive Maintenance in Industry 4.0
Gu, Z. C., Hernandez, J. E., Cook, T., Burtenshaw, J., Scott, S., & Couch, C. (2026) · IEEE International Conference on AI and Data Analytics (ICAD) · doi:10.1109/icad69378.2026.11608648
Tolo, S., Andrews, J., Thatcher, I., et al. (2026) · Proceedings of the Institution of Mechanical Engineers Part O Journal of Risk and Reliability · doi:10.1177/1748006x261467089
A literature review on opinion leaders detection in social networks: approaches, methods and metrics
Chebil, M., Tobji, M. A. B., & Jallouli, R. (2026) · Discover Computing · doi:10.1007/s10791-026-10414-4
“Accordingly, Markov chains are frequently used to model processes where the probability of an event is determined solely by the preceding state [78].”
GIS-INTEGRATED MARKOV CHAIN APPROACH FOR PREDICTING FUTURE OLIVE GROVE LAND USE PATTERNS
Sarı, F. (2026) · Konya Journal of Engineering Sciences · doi:10.36306/konjes.1856563
Dynamic Loss Rate Prediction for Production Materials Based on AHP-Gray Markov
Ma, H., Liu, C., & Wang, X. (2026) · Applied Sciences · doi:10.3390/app16199609
Metadata
- Authors
- Gagniuc, P. A.
- Corresponding author
- Gagniuc, Paul A
- ORCID
- Gagniuc, Paul A
- Venue
- Wiley eBooks
- Publisher
- Wiley
- Published
- 2017-06-22
- OpenAlex
- W4235646468
- Cited by
- 415
- References
- 0
- Citations by year
- 2026: 19 · 2025: 37 · 2024: 64 · 2023: 60 · 2022: 54 · 2021: 68 · 2020: 58 · 2019: 38 · 2018: 17
- FWCI
- 7.99
- Type
- book
- Language
- en
- Open access
- closed
- Locations
- Wiley eBooks (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Probability and Statistical Research
- Physical Sciences › Mathematics › Statistics and Probability › Markov Chains and Monte Carlo Methods
- Physical Sciences › Mathematics › Mathematical Physics › Stochastic processes and statistical mechanics
- Keywords
- Markov chains, stochastic processes, transition probabilities, Markov property
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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