English
Related papers

Related papers: Averaging for a Fully-Coupled Piecewise Determinis…

200 papers

We are interested in the dynamic of a structured branching population where the trait of each individual moves according to a Markov process. The rate of division of each individual is a function of its trait and when a branching event…

Probability · Mathematics 2018-11-20 Aline Marguet

We introduce a method for computing probabilities for spontaneous activity and propagation fail- ure of the action potential in spatially extended, conductance-based neuronal models subject to channel noise, based on statistical properties…

Neurons and Cognition · Quantitative Biology 2020-01-16 Martin Sauer , Wilhelm Stannat

We study optimal control problems in infinite horizon when the dynamics belong to a specific class of piecewise deterministic Markov processes constrained to star-shaped networks (inspired by traffic models). We adapt the results in [H. M.…

Optimization and Control · Mathematics 2015-10-06 Dan Goreac , Magdalena Kobylanski , Miguel Martinez

We have proposed a generalized Langevin-type rate-code model subjected to multiplicative noise, in order to study stationary and dynamical properties of an ensemble containing {\it finite} $N$ neurons. Calculations using the Fokker-Planck…

Disordered Systems and Neural Networks · Physics 2009-11-11 Hideo Hasegawa

We consider additive functionals of Markov processes in continuous time with general (metric) state spaces. We derive concentration bounds for their exponential moments and moments of finite order. Applications include diffusions,…

Probability · Mathematics 2022-02-18 Frank Redig , Florian Völlering

A quantitative description of pulses and wave trains in the spatially discrete Hodgkin-Huxley model for myelinated nerves is given. Predictions of the shape and speed of the waves and the thresholds for propagation failure are obtained. Our…

Neurons and Cognition · Quantitative Biology 2009-11-11 A. Carpio

Piecewise-deterministic Markov process (PDMP) samplers constitute a state-of-the-art Markov chain Monte Carlo paradigm in Bayesian computation, with examples including the zig-zag and bouncy particle sampler (bps). Recent work on the…

Computation · Statistics 2026-03-10 Andrew Chin , Akihiko Nishimura

The paper proposes a class of financial market models which are based on inhomogeneous telegraph processes and jump diffusions with alternating volatilities. It is assumed that the jumps occur when the tendencies and volatilities are…

Pricing of Securities · Quantitative Finance 2008-12-04 Nikita Ratanov

Many processes, such as discrete event systems in engineering or population dynamics in biology, evolve in discrete space and continuous time. We consider the problem of optimal decision making in such discrete state and action space…

Machine Learning · Computer Science 2020-10-27 Bastian Alt , Matthias Schultheis , Heinz Koeppl

Fueled in part by recent applications in neuroscience, the multivariate Hawkes process has become a popular tool for modeling the network of interactions among high-dimensional point process data. While evaluating the uncertainty of the…

Machine Learning · Statistics 2020-07-16 Xu Wang , Mladen Kolar , Ali Shojaie

A dynamical mean-field approximation (DMA) previously proposed by the present author [H. Hasegawa, Phys. Rev E {\bf 67}, 041903 (2003)] has been extended to ensembles described by a general noisy spiking neuron model. Ensembles of $N$-unit…

Disordered Systems and Neural Networks · Physics 2009-11-10 Hideo Hasegawa

We propose a rumor propagation model in which individuals within a homogeneously mixed population can assume one of infinitely many possible states. To analyze this model, we extend the classical law of large numbers for density-dependent…

Probability · Mathematics 2025-08-12 Cristian F. Coletti , Denis A. Luiz , Alejandra Rada

For a wide class of continuous-time Markov processes, including all irreducible hypoelliptic diffusions evolving on an open, connected subset of $\RL^d$, the following are shown to be equivalent: (i) The process satisfies (a slightly weaker…

Probability · Mathematics 2016-04-27 Ioannis Kontoyiannis , Sean P. Meyn

The Hierarchical Dirichlet Process Hidden Markov Model (HDP-HMM) has been used widely as a natural Bayesian nonparametric extension of the classical Hidden Markov Model for learning from sequential and time-series data. A sticky extension…

Machine Learning · Statistics 2020-06-23 Ding Zhou , Yuanjun Gao , Liam Paninski

Neuronal circuits arise as axons and dendrites extend, navigate, and connect to target cells. Axonal growth, in particular, integrates deterministic guidance from substrate mechanics and geometry with stochastic fluctuations generated by…

Biological Physics · Physics 2025-10-10 Cristian Staii

This paper is devoted to the nonparametric estimation of the jump rate and the cumulative rate for a general class of non-homogeneous marked renewal processes, defined on a separable metric space. In our framework, the estimation needs only…

Statistics Theory · Mathematics 2015-06-04 Romain Azaïs , François Dufour , Anne Gégout-Petit

Let $(X_t)_{t = 0 }^{\infty}$ be an irreducible reversible discrete time Markov chain on a finite state space $\Omega $. Denote its transition matrix by $P$. To avoid periodicity issues (and thus ensuring convergence to equilibrium) one…

Probability · Mathematics 2018-01-29 Jonathan Hermon , Yuval Peres

A piecewise-deterministic Markov process, specified by random jumps and switching semi-flows, as well as the associated Markov chain given by its post-jump locations, are investigated in this paper. The existence of an exponentially…

Probability · Mathematics 2020-12-07 Dawid Czapla , Katarzyna Horbacz , Hanna Wojewódka-Ściążko

The generalized Hastings-McLeod solutions to the inhomogeneous Painlev\'{e}-II equation arise in multi-critical unitary random matrix ensembles, the chiral two-matrix model for rectangular matrices, non-intersecting squared Bessel paths,…

Mathematical Physics · Physics 2024-04-15 Kurt Schmidt , Robert Buckingham

Round-Trip Times are one of the most commonly collected performance metrics in computer networks. Measurement platforms such as RIPE Atlas provide researchers and network operators with an unprecedented amount of historical Internet delay…

Networking and Internet Architecture · Computer Science 2019-10-29 Maxime Mouchet , Sandrine Vaton , Thierry Chonavel , Emile Aben , Jasper den Hertog