Tree crown extraction using marked point processes. - Guillaume Perrin; Xavier Descombes; Josiane Zerubia (EUSIPCO, 2004)

Adaptive Simulated Annealing for Energy Minimization Problem in a Marked Point Process Application. - Guillaume Perrin; Xavier Descombes; Josiane Zerubia (EMMCVPR, 2005)

A marked point process model for tree crown extraction in plantations. - Guillaume Perrin; Xavier Descombes; Josiane Zerubia (ICIP (1), 2005)

2D and 3D Vegetation Resource Parameters Assessment using Marked Point Processes. - Guillaume Perrin; Xavier Descombes; Josiane Zerubia (ICPR (1), 2006)

Etude du couvert forestier par processus ponctuels marqués. (Tree crown extraction using Marked Point Processes). - Guillaume Perrin (2006)

Identification of Polynomial Chaos Representations in High Dimension from a Set of Realizations. - Guillaume Perrin; Christian Soize; Denis Duhamel; C. Funfschilling (SIAM J. Sci. Comput., 2012)

Karhunen-Loève expansion revisited for vector-valued random fields: Scaling, errors and optimal basis. - Guillaume Perrin; Christian Soize; Denis Duhamel; C. Funfschilling (J. Comput. Phys., 2013)

A Posteriori Error and Optimal Reduced Basis for Stochastic Processes Defined by a Finite Set of Realizations. - Guillaume Perrin; Christian Soize; Denis Duhamel; C. Funfschilling (SIAM/ASA J. Uncertain. Quantification, 2014)

Active learning surrogate models for the conception of systems with multiple failure modes. - Guillaume Perrin (Reliab. Eng. Syst. Saf., 2016)

Nested polynomial trends for the improvement of Gaussian process-based predictors. - Guillaume Perrin; Christian Soize; Sophie Marque-Pucheu; Josselin Garnier (J. Comput. Phys., 2017)

A Deep Reinforcement Learning Approach for Early Classification of Time Series. - Coralie Martinez; Guillaume Perrin; Emmanuel Ramasso; Michèle Rombaut (EUSIPCO, 2018)

Data-driven kernel representations for sampling with an unknown block dependence structure under correlation constraints. - Guillaume Perrin; Christian Soize; N. Ouhbi (Comput. Stat. Data Anal., 2018)

Efficient Evaluation of Reliability-Oriented Sensitivity Indices. - Guillaume Perrin; G. Defaux (J. Sci. Comput., 2019)

An efficient dimension reduction for the Gaussian process emulation of two nested codes with functional outputs. - Sophie Marque-Pucheu; Guillaume Perrin; Josselin Garnier (Comput. Stat., 2020)

Adaptive method for indirect identification of the statistical properties of random fields in a Bayesian framework. - Guillaume Perrin; Christian Soize (Comput. Stat., 2020)

Group Kernels for Gaussian Process Metamodels with Categorical Inputs. - Olivier Roustant; Esperan Padonou; Yves Deville; Aloïs Clément; Guillaume Perrin; Jean Giorla; Henry P. Wynn (SIAM/ASA J. Uncertain. Quantification, 2020)

Adaptive early classification of temporal sequences using deep reinforcement learning. - Coralie Martinez; Emmanuel Ramasso; Guillaume Perrin; Michèle Rombaut (Knowl. Based Syst., 2020)

Adaptive calibration of a computer code with time-series output. - Guillaume Perrin (Reliab. Eng. Syst. Saf., 2020)

Point process-based approaches for the reliability analysis of systems modeled by costly simulators. - Guillaume Perrin (Reliab. Eng. Syst. Saf., 2021)

Water and air quality monitoring with multiparameter chemical sensors Managing non-idealities from lab to field. - Bérengère Lebental; Stephane Bila; Eric Cloutet; Corinne Dejous; Hamida Hallil; Stéphane Laporte; Bernard Bobby Ngoune; Guillaume Perrin; Yan Ulanowski (IEEE SENSORS, 2022)

Uncertainty-based performance evaluation of a carbon nanotube-based sensor array monitoring pH and active chlorine in drink water. - Bérengère Lebental; Guillaume Perrin (ISOEN, 2022)

A comparison of mixed-variables Bayesian optimization approaches. - Jhouben Cuesta-Ramirez; Rodolphe Le Riche; Olivier Roustant; Guillaume Perrin; Cédric Durantin; Alain Glière (Adv. Model. Simul. Eng. Sci., 2022)

Boosted optimal weighted least-squares. - Cécile Haberstich; Anthony Nouy; Guillaume Perrin (Math. Comput., 2022)

A Calibration Process for Environmental Sensor Array Supporting Uncertainties and Unknown Perturbing Factors: Performances on Simulated and Real Data. - Marine Dumon; Bérengère Lebental; Guillaume Perrin (SENSORS, 2023)

Active Learning of Tree Tensor Networks using Optimal Least Squares. - Cécile Haberstich; Anthony Nouy; Guillaume Perrin (SIAM/ASA J. Uncertain. Quantification, 2023)

Joint Outdoor Ozone and Carbon Monoxide Prediction with a Carbon Nanotube Sensor Array Calibrated Using a Bayesian Framework. - Marine Dumon; Guillaume Perrin; Bérengère Lebental (IEEE SENSORS, 2024)

Bayesian optimization with derivatives acceleration. - Guillaume Perrin; Rodolphe Le Riche (Trans. Mach. Learn. Res., 2024)