Christophe Gonzales

According to our database1, Christophe Gonzales authored at least 55 papers between 1998 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
A Full DAG Score-Based Algorithm for Learning Causal Bayesian Networks with Latent Confounders.
Proceedings of the ECAI 2024 - 27th European Conference on Artificial Intelligence, 19-24 October 2024, Santiago de Compostela, Spain, 2024

2022
A Hybrid Algorithm for Learning Causal Networks using Uncertain Experts' Knowledge.
Proceedings of the International Conference on Probabilistic Graphical Models, 2022

2021
Constraint-Based Bayesian Network Structure Learning using Uncertain Experts' Knowledge.
Proceedings of the Thirty-Fourth International Florida Artificial Intelligence Research Society Conference, 2021

2020
aGrUM/pyAgrum : a toolbox to build models and algorithms for Probabilistic Graphical Models in Python.
Proceedings of the International Conference on Probabilistic Graphical Models, 2020

Decision Under Uncertainty.
Proceedings of the A Guided Tour of Artificial Intelligence Research: Volume I: Knowledge Representation, 2020

Multicriteria Decision Making.
Proceedings of the A Guided Tour of Artificial Intelligence Research: Volume I: Knowledge Representation, 2020

2019
Action Generation Adapted to Low-Level and High-Level Robot-Object Interaction States.
Frontiers Neurorobotics, 2019

Dealing with Continuous Variables in Graphical Models.
Proceedings of the Scalable Uncertainty Management - 13th International Conference, 2019

2018
Apprentissage et sélection de réseaux bayésiens dynamiques pour les processus online non stationnaires.
Rev. d'Intelligence Artif., 2018

Inférence incrémentale pour les modèles.
Rev. d'Intelligence Artif., 2018

On conditional truncated densities Bayesian networks.
Int. J. Approx. Reason., 2018

An empirical study of testing independencies in Bayesian networks using rp-separation.
Int. J. Approx. Reason., 2018

On a simple method for testing independencies in Bayesian networks.
Comput. Intell., 2018

Improving Probabilistic Rules Compilation using PRM.
Proceedings of the Doctoral Consortium and Challenge @ RuleML+RR 2018 hosted by 2nd International Joint Conference on Rules and Reasoning (RuleML+RR 2018), 2018

2017
aGrUM: A Graphical Universal Model Framework.
Proceedings of the Advances in Artificial Intelligence: From Theory to Practice, 2017

Iterative affordance learning with adaptive action generation.
Proceedings of the 2017 Joint IEEE International Conference on Development and Learning and Epigenetic Robotics, 2017

Learning and Selection of Dynamic Bayesian Networks for Non-Stationary Processes in Real Time.
Proceedings of the Thirtieth International Florida Artificial Intelligence Research Society Conference, 2017

2016
A survey of datasets for visual tracking.
Mach. Vis. Appl., 2016

Business Rules Uncertainty Management with Probabilistic Relational Models.
Proceedings of the Rule Technologies. Research, Tools, and Applications, 2016

Real Time Learning of Non-stationary Processes with Dynamic Bayesian Networks.
Proceedings of the Information Processing and Management of Uncertainty in Knowledge-Based Systems, 2016

Incremental Junction Tree Inference.
Proceedings of the Information Processing and Management of Uncertainty in Knowledge-Based Systems, 2016

Bayesian Networks with Conditional Truncated Densities.
Proceedings of the Twenty-Ninth International Florida Artificial Intelligence Research Society Conference, 2016

Testing Independencies in Bayesian Networks with i-Separation.
Proceedings of the Twenty-Ninth International Florida Artificial Intelligence Research Society Conference, 2016

Video Event Detection Based Non-stationary Bayesian Networks.
Proceedings of the Advanced Concepts for Intelligent Vision Systems, 2016

2015
Performance guarantees for a scheduling problem with common stepwise job payoffs.
Theor. Comput. Sci., 2015

Combinatorial Resampling Particle Filter: An Effective and Efficient Method for Articulated Object Tracking.
Int. J. Comput. Vis., 2015

Multivariate Cluster-Based Discretization for Bayesian Network Structure Learning.
Proceedings of the Scalable Uncertainty Management - 9th International Conference, 2015

Bootstrapping interactions with objects from raw sensorimotor data: A novelty search based approach.
Proceedings of the 2015 Joint IEEE International Conference on Development and Learning and Epigenetic Robotics, 2015

A New Algorithm for Learning Non-Stationary Dynamic Bayesian Networks With Application to Event Detection.
Proceedings of the Twenty-Eighth International Florida Artificial Intelligence Research Society Conference, 2015

2014
Uncertain Reasoning for Business Rules.
Proceedings of the RuleML 2014 Challenge and the RuleML 2014 Doctoral Consortium hosted by the 8th International Web Rule Symposium, 2014

An Efficient Bayesian Network Structure Learning Algorithm in the Presence of Deterministic Relations.
Proceedings of the ECAI 2014 - 21st European Conference on Artificial Intelligence, 18-22 August 2014, Prague, Czech Republic, 2014

2013
Single machine scheduling with delivery dates and cumulative payoffs.
J. Sched., 2013

Estimation de densités non paramétriques et multimodales par permutation de sous-particules. Application au suivi d'un ou de plusieurs objets synthétiques articulés.
Rev. d'Intelligence Artif., 2013

Speeding-up structured probabilistic inference using pattern mining.
Int. J. Approx. Reason., 2013

Sub-sample swapping for sequential Monte Carlo approximation of high-dimensional densities in the context of complex object tracking.
Int. J. Approx. Reason., 2013

Hierarchical Annealed Particle Swarm Optimization for Articulated Object Tracking.
Proceedings of the Computer Analysis of Images and Patterns, 2013

2012
DBN-Based Combinatorial Resampling for Articulated Object Tracking.
Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, 2012

Fast multiple histogram computation using Kruskal's algorithm.
Proceedings of the 19th IEEE International Conference on Image Processing, 2012

Min-Space Integral Histogram.
Proceedings of the Computer Vision - ECCV 2012, 2012

An optimized DBN-based mode-focussing particle filter.
Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012

2011
Decision making with multiple objectives using GAI networks.
Artif. Intell., 2011

Patterns Discovery for Efficient Structured Probabilistic Inference.
Proceedings of the Scalable Uncertainty Management - 5th International Conference, 2011

Swapping-Based Partitioned Sampling for Better Complex Density Estimation: Application to Articulated Object Tracking.
Proceedings of the Scalable Uncertainty Management - 5th International Conference, 2011

Simultaneous Partitioned Sampling for Articulated Object Tracking.
Proceedings of the Advances Concepts for Intelligent Vision Systems, 2011

2009
Multiobjective Optimization using GAI Models.
Proceedings of the IJCAI 2009, 2009

Fast Recommendations using GAI Models.
Proceedings of the IJCAI 2009, 2009

Choquet Optimization Using GAI Networks for Multiagent/Multicriteria Decision-Making.
Proceedings of the Algorithmic Decision Theory, First International Conference, 2009

Multiattribute Utility Theory.
Proceedings of the Decision-making Process, 2009

2008
Preference Aggregation with Graphical Utility Models.
Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence, 2008

2007
Réseaux GAI pour la prise de décision.
Rev. d'Intelligence Artif., 2007

On Directed and Undirected Propagation Algorithms for Bayesian Networks.
Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2007

2006
Learning Bayesian Networks Structure using Markov Networks.
Proceedings of the Third European Workshop on Probabilistic Graphical Models, 2006

2004
Une unification des algorithmes d'inférence de Pearl et de Jensen.
Rev. d'Intelligence Artif., 2004

GAI Networks for Utility Elicitation.
Proceedings of the Principles of Knowledge Representation and Reasoning: Proceedings of the Ninth International Conference (KR2004), 2004

1998
Imprecise sampling and direct decision making.
Ann. Oper. Res., 1998


  Loading...