Nigel G. Bean

发表

Stochastic 2-dimensional fluid model

Malgorzata M. O'Reilly, Nigel G. Bean, 2012, PERV.

Stochastic model for maintenance in continuously deteriorating systems

Malgorzata M. O'Reilly, Nigel G. Bean, Aviva Samuelson, 2017, Eur. J. Oper. Res..

Modelling systems of reservoirs using structured Markov chains

Phil Howlett, Nigel G. Bean, Simon Beecham, 2010 .

Pachinko Prediction: A Bayesian method for event prediction from social media data pdf

Mehwish Nasim, Nigel G. Bean, Andrew Nguyen, 2018, Inf. Process. Manag..

Performance measures of a multi-layer Markovian fluid model

Malgorzata M. O'Reilly, Nigel G. Bean, N. Bean, 2008, Ann. Oper. Res..

Second-order Markov reward models driven by QBD processes

Yong Ren, Malgorzata M. O'Reilly, Nigel G. Bean, 2012, Perform. Evaluation.

GLaSS: Semi-supervised Graph Labelling with Markov Random Walks to Absorption

Nigel G. Bean, Lewis Mitchell, Simon Jonathan Tuke, 2018, COMPLEX NETWORKS.

Podlab at SemEval-2019 Task 3: The Importance of Being Shallow

Nigel G. Bean, Andrew Nguyen, Lewis Mitchell, 2019, SemEval@NAACL-HLT.

The Nature and Origin of Heavy Tails in Retweet Activity

Nigel G. Bean, Giang T. Nguyen, Lewis Mitchell, 2017, WWW.

SMERC: Social media event response clustering using textual and temporal information

Nigel G. Bean, Giang T. Nguyen, Lewis Mitchell, 2018, 2018 IEEE International Conference on Big Data (Big Data).

Spatially-coherent uniformization of a stochastic fluid model to a Quasi-Birth-and-Death process

Malgorzata M. O'Reilly, Nigel G. Bean, 2013, Perform. Evaluation.

Doubling algorithms for stationary distributions of fluid queues: A probabilistic interpretation

Federico Poloni, Nigel G. Bean, Giang T. Nguyen, 2018, Perform. Evaluation.

A framework for streamlined statistical prediction using topic models pdf

Nigel G. Bean, Lewis Mitchell, Simon Jonathan Tuke, 2019, LaTeCH@NAACL-HLT.

Semi-supervised graph labelling reveals increasing partisanship in the United States Congress

Nigel G. Bean, Lewis Mitchell, Simon Jonathan Tuke, 2019, Applied Network Science.

A stochastic fluid model driven by an uncountable-state process, which is a stochastic fluid model itself: the stochastic fluid-fluid model

Malgorzata M. O'Reilly, Nigel G. Bean, 2012, PERV.

An induced natural selection heuristic for finding optimal Bayesian experimental designs

Nigel G. Bean, David J. Price, Simon Jonathan Tuke, 2017, Comput. Stat. Data Anal..

Analysis of queues with rational arrival process components: a general approach

Bo Friis Nielsen, Nigel G. Bean, N. Bean, 2012, PERV.

Robust connection acceptance control for ATM networks with incomplete source information

Nigel G. Bean, N. Bean, 1994, Ann. Oper. Res..

Markovian trees: properties and algorithms

Nigel G. Bean, Peter G. Taylor, Nectarios Kontoleon, 2008, Ann. Oper. Res..

On Binomial Observations of Continuous-Time Markovian Population Models

Nigel G. Bean, Ali Eshragh, Robert Elliott, 2015, J. Appl. Probab..

Yaglom limit for stochastic fluid models

Nigel G. Bean, Zbigniew Palmowski, Małgorzata M. O’Reilly, 2021, Advances in Applied Probability.

RAP-modulated fluid processes: First passages and the stationary distribution

Nigel G. Bean, Giang T. Nguyen, Oscar Peralta, 2021, Stochastic Processes and their Applications.

The quasi-stationary behavior of quasi-birth-and-death processes

Nigel G. Bean, Peter G. Taylor, Guy Latouche, 1997 .

Hitting probabilities and hitting times for stochastic fluid flows

Nigel G. Bean, Peter G. Taylor, Małgorzata M. O’Reilly, 2005 .

Characterization of Matrix-Exponential Distributions

Nigel G. Bean, Mark Fackrell, P. Taylor, 2008 .

A Stochastic Two-Dimensional Fluid Model

Nigel G. Bean, Małgorzata M. O’Reilly, N. Bean, 2013 .

On the generalized reward generator for stochastic fluid models: A new equation for Ψ

Nigel G. Bean, Aviva Samuelson, Małgorzata M. O’Reilly, 2017 .

HITTING PROBABILITIES AND HITTING TIMES FOR STOCHASTIC FLUID FLOWS: THE BOUNDED MODEL

Nigel G. Bean, Peter G. Taylor, Małgorzata M. O’Reilly, 2008, Probability in the Engineering and Informational Sciences.

The output process of an MMPP/M/1 queue

Nigel G. Bean, Peter G. Taylor, P. Taylor, 1998, Journal of Applied Probability.

Quasi-reversibility and quasi-birth-and-death processes

Nigel G. Bean, Peter G. Taylor, Guy Latouche, 1998 .

When is a MAP poisson

Nigel G. Bean, N. Bean, David Green, 2000 .

Approximations to quasi-birth-and-death processes with infinite blocks

Nigel G. Bean, Guy Latouche, G. Latouche, 2010, Advances in Applied Probability.

Quasi-Birth-and-Death Processes with Rational Arrival Process Components

Bo Friis Nielsen, Nigel G. Bean, N. G. Bean, 2010 .

The stochastic fluid–fluid model: A stochastic fluid model driven by an uncountable-state process, which is a stochastic fluid model itself ☆

Nigel G. Bean, Małgorzata M. O’Reilly, 2014 .

Dynamic and equilibrium behavior of controlled loss networks

Stan Zachary, Nigel G. Bean, Richard J. Gibbens, 1997 .

Some asymptotic properties of two-stage tandem networks of PH/PH/1 queues

Nigel G. Bean, Peter G. Taylor, P. Taylor, 1998 .

Algorithms for the Laplace–Stieltjes Transforms of First Return Times for Stochastic Fluid Flows

Nigel G. Bean, Peter G. Taylor, Małgorzata M. O’Reilly, 2008 .