Nonequilibrium steady states of matrix-product form: a solver's guide
We consider the general problem of determining the steady state of stochastic
nonequilibrium systems such as those that have been used to model (among other things) …
nonequilibrium systems such as those that have been used to model (among other things) …
The nested chinese restaurant process and bayesian nonparametric inference of topic hierarchies
We present the nested Chinese restaurant process (nCRP), a stochastic process that
assigns probability distributions to ensembles of infinitely deep, infinitely branching trees …
assigns probability distributions to ensembles of infinitely deep, infinitely branching trees …
[BOOK][B] Probability models for DNA sequence evolution
R Durrett, R Durrett - 2008 - Springer
Our basic question is: Given a collection of DNA sequences, what underlying forces are
responsible for the observed patterns of variability? To approach this question we introduce …
responsible for the observed patterns of variability? To approach this question we introduce …
[BOOK][B] Risk-neutral valuation: Pricing and hedging of financial derivatives
NH Bingham, R Kiesel - 2013 - books.google.com
Since its introduction in the early 1980s, the risk-neutral valuation principle has proved to be
an important tool in the pricing and hedging of financial derivatives. Following the success of …
an important tool in the pricing and hedging of financial derivatives. Following the success of …
Sleep exerts lasting effects on hematopoietic stem cell function and diversity
CS McAlpine, MG Kiss, FM Zuraikat, D Cheek… - Journal of Experimental …, 2022 - rupress.org
A sleepless night may feel awful in its aftermath, but sleep's revitalizing powers are
substantial, perpetuating the idea that convalescent sleep is a consequence-free …
substantial, perpetuating the idea that convalescent sleep is a consequence-free …
Reinforcement learning for temporal logic control synthesis with probabilistic satisfaction guarantees
We present a model-free reinforcement learning algorithm to synthesize control policies that
maximize the probability of satisfying high-level control objectives given as Linear Temporal …
maximize the probability of satisfying high-level control objectives given as Linear Temporal …
Modular deep reinforcement learning for continuous motion planning with temporal logic
This letter investigates the motion planning of autonomous dynamical systems modeled by
Markov decision processes (MDP) with unknown transition probabilities over continuous …
Markov decision processes (MDP) with unknown transition probabilities over continuous …
Stability analysis and connected vehicles management for mixed traffic flow with platoons of connected automated vehicles
Y Qin, Q Luo, H Wang - Transportation Research Part C: Emerging …, 2023 - Elsevier
Recently, the market has witnessed the emergence of intelligent vehicles equipped with
diverse functionalities. Among these are connected automated vehicles (CAVs) boasting a …
diverse functionalities. Among these are connected automated vehicles (CAVs) boasting a …
Understanding markov chains
N Privault - Examples and Applications, Publisher Springer-Verlag …, 2013 - Springer
Stochastic and Markovian modeling are of importance to many areas of science including
physics, biology, engineering, as well as economics, finance, and social sciences. This text …
physics, biology, engineering, as well as economics, finance, and social sciences. This text …
A learning based approach to control synthesis of markov decision processes for linear temporal logic specifications
We propose to synthesize a control policy for a Markov decision process (MDP) such that the
resulting traces of the MDP satisfy a linear temporal logic (LTL) property. We construct a …
resulting traces of the MDP satisfy a linear temporal logic (LTL) property. We construct a …