World's Best Scientists 2026 revealed!
Pierre Bessière

Pierre Bessière

D-Index & Metrics

Computer Science

D-Index
30
Citations
3970
World Ranking
14086
National Ranking
382

Overview

Pierre Bessière is affiliated with the Centre national de la recherche scientifique (CNRS) in France. Their research primarily spans the field of Engineering, with a particular focus on Electrical and Electronic Engineering.

The scientist's recent publications cover topics related to Bayesian machines implemented with memristors, as well as epidemiological studies concerning infectious diseases. Their notable papers include:

  • A memristor-based Bayesian machine, 2022, Nature Electronics
  • A Memristor-Based Bayesian Machine, 2021, arXiv (Cornell University)
  • High pathogenicity avian influenza A (H5N1) clade 2.3.4.4b virus infection in a captive Tibetan black bear (Ursus thibetanus): investigations based on paraffin-embedded tissues, France, 2022, 2023, bioRxiv (Cold Spring Harbor Laboratory)
  • The Logarithmic Memristor-Based Bayesian Machine, 2024, arXiv (Cornell University)

They collaborate frequently with several coauthors, including:

  • Kamel-Eddine Harabi
  • Tifenn Hirtzlin
  • Clément Turck
  • Elisa Vianello
  • Raphaël Laurent

Their research has been disseminated mainly through the following venues:

  • arXiv (Cornell University)
  • Nature Electronics
  • bioRxiv (Cold Spring Harbor Laboratory)

The main and subfields of study encompassing their work include:

  • Engineering
  • Electrical and Electronic Engineering
  • Cellular and Molecular Neuroscience
  • Epidemiology
  • Agronomy and Crop Science
  • Infectious Diseases

The core topics of their research involve:

  • Advanced Memory and Neural Computing
  • Ferroelectric and Negative Capacitance Devices
  • Neuroscience and Neural Engineering
  • Radiation Effects in Electronics
  • Influenza Virus Research Studies
  • Animal Disease Management and Epidemiology
  • Viral gastroenteritis research and epidemiology

Best Publications

  • Bayesian Occupancy Filtering for Multitarget Tracking: An Automotive Application

    Christophe Coué;Cédric Pradalier;Christian Laugier;Thierry Fraichard

  • Bayesian Robot Programming

    Olivier Lebeltel;Pierre Bessière;Julien Diard;Emmanuel Mazer

  • The "Ariadne's clew" algorithm: global planning with local methods

    P. Bessiere;J.-M. Ahuactzin;E.-G. Talbi;E. Mazer

  • The Ariadne's clew algorithm

    Emmanuel Mazer;Juan Manuel Ahuactzin;Pierre Bessiére

  • Skyrmion Gas Manipulation for Probabilistic Computing

    D. Pinna;F. Abreu Araujo;Joo-Von Kim;Vincent Cros

  • A parallel genetic algorithm for the graph partitioning problem

    E.-G. Talbi;P. Bessière

  • Using genetic algorithms for robot motion planning

    Juan Manuel Ahuactzin;El-Ghazali Talbi;Pierre Bessière;Emmanuel Mazer

  • A Bayesian model for opening prediction in RTS games with application to StarCraft

    Gabriel Synnaeve;Pierre Bessiere

  • Bayesian Programming

    Pierre Bessiere;Emmanuel Mazer;Juan Manuel Ahuactzin;Kamel Mekhnacha

  • Teaching Bayesian Behaviours to Video Game Characters

    Ronan Le Hy;Anthony Arrigoni;Pierre Bessière;Olivier Lebeltel

  • A Bayesian model for plan recognition in RTS games applied to StarCraft

    Gabriel Synnaeve;Pierre Bessière

  • The CyCab: a car-like robot navigating autonomously and safely among pedestrians

    Cédric Pradalier;Jorge Hermosillo;Carla Koike;Christophe Braillon

  • Common Bayesian Models for Common Cognitive Issues

    Francis Colas;Julien Diard;Pierre Bessière

  • Multi-sensor data fusion using Bayesian programming : an automotive application

    C. Coue;Th. Fraichard;P. Bessiere;E. Mazer

  • A Bayesian model for RTS units control applied to StarCraft

    Gabriel Synnaeve;Pierre Bessiere

  • Adverse conditions improve distinguishability of auditory, motor and perceptuo-motor theories of speech perception: an exploratory Bayesian modeling study

    Clément Moulin-Frier;Raphaël Laurent;Pierre Bessière;Jean-Luc Schwartz

  • COSMO (“Communicating about Objects using Sensory–Motor Operations”): A Bayesian modeling framework for studying speech communication and the emergence of phonological systems

    Clément Moulin-Frier;Clément Moulin-Frier;Julien Diard;Jean-Luc Schwartz;Pierre Bessière

  • A Survey of Probabilistic Models Using the Bayesian Programming Methodology as a Unifying Framework

    Julien Diard;Pierre Bessiere;Emmanuel Mazer

  • A procedural logic

    Michael P. Georgeff;Amy L. Lansky;Pierre Bessiere

  • Using Bayesian Programming for multi-sensor multi-target tracking in automotive applications

    C. Coue;Th. Fraichard;P. Bessiere;E. Mazer

  • The “Ariadne's clew” algorithm: global planning with local methods

    Pierre Bessière;Juan-Manuel Ahuactzin;El-Ghazali Talbi;Emmanuel Mazer

Frequent Co-Authors

Jean-Luc Schwartz
Jean-Luc Schwartz Centre national de la recherche scientifique, CNRS
El-Ghazali Talbi
El-Ghazali Talbi University of Lille
Christian Laugier
Christian Laugier French Institute for Research in Computer Science and Automation - INRIA
Gabriel Synnaeve
Gabriel Synnaeve Facebook (United States)
Damien Querlioz
Damien Querlioz University of Paris-Saclay
Thierry Fraichard
Thierry Fraichard French Institute for Research in Computer Science and Automation - INRIA
Vincent Cros
Vincent Cros University of Paris-Saclay
Alain Berthoz
Alain Berthoz Collège de France
Miguel Castelo-Branco
Miguel Castelo-Branco University of Coimbra

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