Mammalian CpG islands are key epigenomic elements that were first characterized
experimentally as genomic fractions with low levels of DNA methylation. Currently, CpG …

Markov jump processes (or continuous-time Markov chains) are a simple and important
class of continuous-time dynamical systems. In this paper, we tackle the problem of …

Markov jump processes are continuous-time stochastic processes with a wide range of
applications in both natural and social sciences. Despite their widespread use, inference in …

The marginal likelihood of a model is a key quantity for assessing the evidence provided by
the data in support of a model. The marginal likelihood is the normalizing constant for the …

We consider continuous time Markovian processes where populations of individual agents
interact stochastically according to kinetic rules. Despite the increasing prominence of such …

This paper addresses the problem of statistical inference for latent continuous-time
stochastic processes, which is often intractable, particularly for discrete state space …

Disconnecting impaired or suspicious nodes and rewiring to those reliable, adaptive
networks have the potential to inhibit cascading failures, such as DDoS attack and computer …

Markov jump processes and continuous time Bayesian networks are important classes of
continuous time dynamical systems. In this paper, we tackle the problem of inferring …

Safety causation analysis is of paramount importance in socio-technical systems, playing a
crucial role in identifying and mitigating potential hazards and risks to ensure safe and …

In this paper, we present a method for reducing a regular, discrete-time Markov chain
(DTMC) to another DTMC with a given, typically much smaller number of states. The cost of …