Random assignment versus fixed assignment in multilevel importance splitting for estimating stochastic reach probabilities
From MaRDI portal
Publication:2684914
DOI10.1007/s11009-021-09892-4zbMath1506.60005OpenAlexW4210340294MaRDI QIDQ2684914
Publication date: 17 February 2023
Published in: Methodology and Computing in Applied Probability (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s11009-021-09892-4
Monte Carlo methodinteracting particlesreach probabilitymulti-dimensional diffusion processmultilevel importance splitting
Monte Carlo methods (65C05) Computational methods for problems pertaining to probability theory (60-08)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- An efficient algorithm for rare-event probability estimation, combinatorial optimization, and counting
- Introduction to rare event simulation.
- Hybrid dynamical systems. Observation and control
- Randomized algorithms with splitting: Why the classic randomized algorithms do not work and how to make them work
- Negative association, ordering and convergence of resampling methods
- Multilevel Splitting for Estimating Rare Event Probabilities
- First-passage time of Markov processes to moving barriers
- Rare events, splitting, and quasi-Monte Carlo
- A large deviations perspective on the efficiency of multilevel splitting
- Approximations of Stochastic Hybrid Systems
- Approximate Abstractions of Stochastic Hybrid Systems
- On a class of discrete generation interacting particle systems
This page was built for publication: Random assignment versus fixed assignment in multilevel importance splitting for estimating stochastic reach probabilities