32 citations · 70 across the 10 of their papers we have counts for
12 papers
On the computational cost of Stochastic Gradient Langevin Dynamics
Mateusz B. Majka, Tigran Nagapetyan, Łukasz Szpruch +2
Stochastic Gradient Langevin Dynamics (SGLD) reduces the cost of Langevin-based sampling by replacing full-dataset drift evaluations with mini-batch approximations, but the resulti…
Multilevel Monte Carlo Method for Statistical Model Checking of Hybrid Systems
Sadegh Esmaeil Zadeh Soudjani, Rupak Majumdar, Tigran Nagapetyan
We study statistical model checking of continuous-time stochastic hybrid systems. The challenge in applying statistical model checking to these systems is that one cannot simulate…
Adaptive Multilevel Monte Carlo Approximation of Distribution Functions
Mike B. Giles, Tigran Nagapetyan, Klaus Ritter
We analyse a multilevel Monte Carlo method for the approximation of distribution functions of univariate random variables. Since, by assumption, the target distribution is not know…
The True Cost of Stochastic Gradient Langevin Dynamics
Tigran Nagapetyan, Andrew B. Duncan, Leonard Hasenclever +3
The problem of posterior inference is central to Bayesian statistics and a wealth of Markov Chain Monte Carlo (MCMC) methods have been proposed to obtain asymptotically correct sam…
Multilevel Monte Carlo for Scalable Bayesian Computations
Mike Giles, Tigran Nagapetyan, Lukasz Szpruch +2
Markov chain Monte Carlo (MCMC) algorithms are ubiquitous in Bayesian computations. However, they need to access the full data set in order to evaluate the posterior density at eve…
Multilevel Monte Carlo for Reliability Theory
Louis J. M. Aslett, Tigran Nagapetyan, Sebastian J. Vollmer
As the size of engineered systems grows, problems in reliability theory can become computationally challenging, often due to the combinatorial growth in the cut sets. In this paper…
Variance reduction for discretised diffusions via regression
Denis Belomestny, Stefan Häfner, Tigran Nagapetyan +1
In this paper we present a novel approach towards variance reduction for discretised diffusion processes. The proposed approach involves specially constructed control variates and…
Variance reduced multilevel path simulation: going beyond the complexity
Denis Belomestny, Tigran Nagapetyan
In this paper a novel modification of the multilevel Monte Carlo approach, allowing for further significant complexity reduction, is proposed. The idea of the modification is to us…
Multilevel path simulation for weak approximation schemes
Denis Belomestny, Tigran Nagapetyan
In this paper we discuss the possibility of using multilevel Monte Carlo (MLMC) methods for weak approximation schemes. It turns out that by means of a simple coupling between cons…
Pricing American options via multi-level approximation methods
Denis Belomestny, Fabian Dickmann, Tigran Nagapetyan
In this article we propose a novel approach to reduce the computational complexity of various approximation methods for pricing discrete time American options. Given a sequence of…
Remarks on the Afriat's theorem and the Monge-Kantorovich problem
Alexander V. Kolesnikov, Olga V. Kudryavtseva, Tigran Nagapetyan
The famous Afriat's theorem from the theory of revealed preferences establishes necessary and suffient conditions for existence of utility function for a given set of choices and p…
About new dynamical interpretations of entropic model of correspondence matrix calculation and Nash-Wardrop's equilibrium in Beckmann's traffic flow distribution model
Tigran Nagapetyan, Evgenia Gasnikova
In this work we widespread statistical physics (chemical kinetic stochastic) approach to the investigation of macrosystems, arise in economic, sociology and traffic flow theory. Th…