How long, O Bayesian network, will I sample thee? : A program analysis perspective on expected sampling times
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
-
Online-Ressource
- Sprache
-
Englisch
- Anmerkungen
-
In: 10.1007/978-3-319-89884-1_7
- Ereignis
-
Veröffentlichung
- (wo)
-
Aachen
- (wer)
-
Universitätsbibliothek der RWTH Aachen
- (wann)
-
2018
- Urheber
- DOI
-
10.18154/RWTH-CONV-236462
- URN
-
urn:nbn:de:101:1-2021040916033634552098
- Rechteinformation
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
25.03.2025, 13:56 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Batz, Kevin
- Kaminski, Benjamin Lucien
- Katoen, Joost-Pieter
- Matheja, Christoph
- Universitätsbibliothek der RWTH Aachen
Entstanden
- 2018
Ähnliche Objekte (12)
Under-Approximating Expected Total Rewards in POMDPs
Concepts, algorithms, and tools for model checking
Accurately Computing Expected Visiting Times and Stationary Distributions in Markov Chains
A Calculus for Amortized Expected Runtimes
Certificates for Probabilistic Pushdown Automata via Optimistic Value Iteration
Formal methods for real time and probabilistic systems : proceedings
Automatically Finding the Right Probabilities in Bayesian Networks
Sound Value Iteration
Fine-Tuning the Odds in Bayesian Networks
Multi-objective Optimization of Long-run Average and Total Rewards
Verification of pointer programs
Foundations of probabilistic programming
Under-Approximating Expected Total Rewards in POMDPs
Concepts, algorithms, and tools for model checking
Accurately Computing Expected Visiting Times and Stationary Distributions in Markov Chains
A Calculus for Amortized Expected Runtimes
Certificates for Probabilistic Pushdown Automata via Optimistic Value Iteration
Formal methods for real time and probabilistic systems : proceedings
Automatically Finding the Right Probabilities in Bayesian Networks
Sound Value Iteration
Fine-Tuning the Odds in Bayesian Networks
Multi-objective Optimization of Long-run Average and Total Rewards
Verification of pointer programs
Foundations of probabilistic programming
Under-Approximating Expected Total Rewards in POMDPs
Concepts, algorithms, and tools for model checking
Accurately Computing Expected Visiting Times and Stationary Distributions in Markov Chains
A Calculus for Amortized Expected Runtimes
Certificates for Probabilistic Pushdown Automata via Optimistic Value Iteration
Formal methods for real time and probabilistic systems : proceedings
Automatically Finding the Right Probabilities in Bayesian Networks
Sound Value Iteration
Fine-Tuning the Odds in Bayesian Networks
Multi-objective Optimization of Long-run Average and Total Rewards
Verification of pointer programs