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Overview

Paul Balister is affiliated with the University of Oxford in the United Kingdom. Their research spans multiple areas within mathematics and computer science, focusing on discrete mathematics, combinatorics, and computational theory. They have a body of work that includes significant contributions to topics such as graph theory, stochastic processes, and analytic number theory.

Their frequent publication venues include:

  • arXiv (Cornell University)
  • Journal of the European Mathematical Society
  • Random Structures and Algorithms
  • Inventiones mathematicae
  • Acta Mathematica Academiae Scientiarum Hungaricae

Paul Balister's recent papers are:

  • Subcritical monotone cellular automata, 2023, Random Structures and Algorithms
  • On the Erdős covering problem: the density of the uncovered set, 2021, Inventiones mathematicae
  • Erdős covering systems, 2020, Acta Mathematica Academiae Scientiarum Hungaricae
  • Flat Littlewood polynomials exist, 2020, Annals of Mathematics
  • Improved bounds for 1-independent percolation on Zⁿ, 2025, Electronic Journal of Probability

Their collaborations include frequent co-authors:

  • Béla Bollobás
  • Robert Morris
  • Marius Tiba
  • Julian Sahasrabudhe
  • Alex Scott

Primary fields of study for Paul Balister are Mathematics and Computer Science. Their subfields include:

  • Discrete Mathematics and Combinatorics
  • Computational Theory and Mathematics
  • Statistics and Probability
  • Mathematical Physics
  • Algebra and Number Theory

They focus on several main research themes and topics, including:

  • Limits and Structures in Graph Theory
  • Stochastic processes and statistical mechanics
  • Markov Chains and Monte Carlo Methods
  • Analytic Number Theory Research
  • Cellular Automata and Applications
  • Graph Labeling and Dimension Problems
  • Coding theory and cryptography

Best Publications

  • Adjacent Vertex Distinguishing Edge-Colorings

    P. N. Balister;E. Gyo dblac;J. Lehel

  • Vertex-distinguishing edge colorings of graphs

    P. N. Balister;O. M. Riordan;R. H. Schelp

  • Reliable density estimates for coverage and connectivity in thin strips of finite length

    Paul Balister;Béla Bollobas;Amites Sarkar;Santosh Kumar

  • Phase transitions in the neuropercolation model of neural populations with mixed local and non-local interactions

    Robert Kozma;Marko Puljic;Paul Balister;Bela Bollobás

  • Continuum percolation with steps in the square or the disc

    Paul Balister;Béla Bollobás_aff n;Mark Walters_aff n

  • Connectivity of random k -nearest-neighbour graphs

    Paul Balister;Béla Bollobás;Amites Sarkar;Mark Walters

  • Trap Coverage: Allowing Coverage Holes of Bounded Diameter in Wireless Sensor Networks

    P. Balister;Z. Zheng;S. Kumar;P. Sinha

  • Vertex distinguishing colorings of graphs with Δ(G)=2

    Paul N. Balister;Béla Bollobás;Béla Bollobás;Richard H. Schelp

  • Even-hole-free graphs part I: Decomposition theorem

    Michele Conforti;Gérard Cornuéjols;Ajai Kapoor;Kristina Vušković

  • Random majority percolation

    Paul Balister;Béla Bollobás;J. Robert Johnson;Mark Walters

  • Packing Circuits into K N

    Paul Balister

  • Random vs. Deterministic Deployment of Sensors in the Presence of Failures and Placement Errors

    P. Balister;S. Kumar

  • Neuropercolation: A Random Cellular Automata Approach to Spatio-temporal Neurodynamics

    Robert Kozma;Marko Puljic;Paul Balister;Bela Bollobas

  • Note on Nakayama’s lemma for compact $\Lambda$-modules

    P. N. Balister;S. Howson

  • Subcritical -bootstrap percolation models have non-trivial phase transitions

    Paul Balister;Béla Bollobás;Michał Przykucki;Paul Smith

  • Dependent percolation in two dimensions

    P.N. Balister;B. Bollobás;A.M. Stacey

  • The Interlace Polynomial of Graphs at - 1

    P.N. Balister;B. Bollobás;J. Cutler;L. Pebody

  • Percolation, Connectivity, Coverage and Colouring of Random Geometric Graphs

    Paul Balister;Amites Sarkar;Béla Bollobás;Béla Bollobás

  • Projections, entropy and sumsets

    Paul Balister;Béla Bollobás

  • Large deviations for mean field models of probabilistic cellular automata

    P. Balister;B. Bollobás;R. Kozma

Frequent Co-Authors

Béla Bollobás
Béla Bollobás University of Memphis
Oliver Riordan
Oliver Riordan University of Oxford
Robert Kozma
Robert Kozma University of Memphis
Gregory Gutin
Gregory Gutin Royal Holloway University of London
Zoltán Füredi
Zoltán Füredi University of Illinois at Urbana-Champaign
Anima Anandkumar
Anima Anandkumar Nvidia (United Kingdom)
Anders Yeo
Anders Yeo University of Southern Denmark
Walter J. Freeman
Walter J. Freeman University of California, Berkeley
Martin Haenggi
Martin Haenggi University of Notre Dame

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