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Paul-Henry Cournède
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2020 – today
- 2024
- [j22]Lily Monnier
, Paul-Henry Cournède
:
A novel batch-effect correction method for scRNA-seq data based on Adversarial Information Factorization. PLoS Comput. Biol. 20(2) (2024) - [c16]Paul Dubois, Paul-Henry Cournède
, Nikos Paragios
, Pascal Fenoglietto:
Radiotherapy Dose Optimization via Clinical Knowledge Based Reinforcement Learning. AIME (1) 2024: 151-160 - [i9]Paolo Ballarini, Mahmoud Bentriou, Paul-Henry Cournède:
A Formal Approach for Tuning Stochastic Oscillators. CoRR abs/2405.09183 (2024) - [i8]Mouad El Bouchattaoui, Myriam Tami, Benoit Lepetit, Paul-Henry Cournède:
Causal Contrastive Learning for Counterfactual Regression Over Time. CoRR abs/2406.00535 (2024) - 2023
- [j21]Quentin Blampey
, Nadège Bercovici
, Charles-Antoine Dutertre
, Isabelle Pic, Joana Mourato Ribeiro
, Fabrice André
, Paul-Henry Cournède
:
A biology-driven deep generative model for cell-type annotation in cytometry. Briefings Bioinform. 24(5) (2023) - [j20]Hakim Benkirane
, Yoann Pradat
, Stefan Michiels, Paul-Henry Cournède:
CustOmics: A versatile deep-learning based strategy for multi-omics integration. PLoS Comput. Biol. 19(3) (2023) - [c15]Paolo Ballarini, Mahmoud Bentriou, Paul-Henry Cournède:
A Formal Approach for Tuning Stochastic Oscillators. CMSB 2023: 1-17 - [c14]Leo Fillioux, Emilie Gontran, Jérôme Cartry, Jacques RR Mathieu, Sabrina Bedja, Alice Boilève, Paul-Henry Cournède, Fanny Jaulin, Stergios Christodoulidis, Maria Vakalopoulou:
Spatio-Temporal Analysis of Patient-Derived Organoid Videos Using Deep Learning for the Prediction of Drug Efficacy. ICCV (Workshops) 2023: 3932-3941 - [c13]Leo Fillioux, Joseph Boyd, Maria Vakalopoulou, Paul-Henry Cournède, Stergios Christodoulidis:
Structured State Space Models for Multiple Instance Learning in Digital Pathology. MICCAI (1) 2023: 594-604 - [i7]Leo Fillioux, Joseph Boyd, Maria Vakalopoulou, Paul-Henry Cournède, Stergios Christodoulidis:
Structured State Space Models for Multiple Instance Learning in Digital Pathology. CoRR abs/2306.15789 (2023) - [i6]Leo Fillioux, Emilie Gontran, Jérôme Cartry, Jacques RR Mathieu, Sabrina Bedja, Alice Boilève, Paul-Henry Cournède, Fanny Jaulin, Stergios Christodoulidis, Maria Vakalopoulou:
Spatio-Temporal Analysis of Patient-Derived Organoid Videos Using Deep Learning for the Prediction of Drug Efficacy. CoRR abs/2308.14461 (2023) - [i5]Mouad El Bouchattaoui, Myriam Tami, Benoit Lepetit, Paul-Henry Cournède:
Causal Dynamic Variational Autoencoder for Counterfactual Regression in Longitudinal Data. CoRR abs/2310.10559 (2023) - 2022
- [j19]Martin Charachon
, Paul-Henry Cournède
, Céline Hudelot
, Roberto Ardon:
Leveraging conditional generative models in a general explanation framework of classifier decisions. Future Gener. Comput. Syst. 132: 223-238 (2022) - [j18]Gautier Viaud
, Prasanna Mayilvahanan, Paul-Henry Cournède
:
Representation Learning for the Clustering of Multi-Omics Data. IEEE ACM Trans. Comput. Biol. Bioinform. 19(1): 135-145 (2022) - [c12]Hakim Benkirane
, Maria Vakalopoulou, Stergios Christodoulidis, Ingrid-Judith Garberis, Stefan Michiels, Paul-Henry Cournède:
Hyper-AdaC: Adaptive clustering-based hypergraph representation of whole slide images for survival analysis. ML4H@NeurIPS 2022: 405-418 - [i4]Quentin Blampey, Nadège Bercovici, Charles-Antoine Dutertre, Isabelle Pic, Fabrice André, Joana Mourato Ribeiro, Paul-Henry Cournède:
Interpretable cytometry cell-type annotation with flow-based deep generative models. CoRR abs/2208.05745 (2022) - [i3]Hakim Benkirane, Yoann Pradat, Stefan Michiels, Paul-Henry Cournède:
CustOmics: A versatile deep-learning based strategy for multi-omics integration. CoRR abs/2209.05485 (2022) - 2021
- [j17]Mahmoud Bentriou
, Paolo Ballarini
, Paul-Henry Cournède
:
Automaton-ABC: A statistical method to estimate the probability of spatio-temporal properties for parametric Markov population models. Theor. Comput. Sci. 893: 191-219 (2021) - [c11]Mathilde Sautreuil
, Sarah Lemler
, Paul-Henry Cournède
:
Neural Networks to Predict Survival from RNA-seq Data in Oncology. CMSB 2021: 122-140 - [c10]Martin Charachon
, Paul-Henry Cournède
, Céline Hudelot, Roberto Ardon:
Visual Explanation by Unifying Adversarial Generation and Feature Importance Attributions. iMIMIC/TDA4MedicalData@MICCAI 2021: 44-55 - [i2]Martin Charachon, Paul-Henry Cournède, Céline Hudelot, Roberto Ardon:
Leveraging Conditional Generative Models in a General Explanation Framework of Classifier Decisions. CoRR abs/2106.10947 (2021) - 2020
- [j16]Chloé Adam, Antoine Aliotti, Fragkiskos D. Malliaros, Paul-Henry Cournède
:
Dynamic monitoring of software use with recurrent neural networks. Data Knowl. Eng. 125: 101781 (2020) - [c9]Martin Charachon
, Céline Hudelot, Paul-Henry Cournède
, Camille Ruppli, Roberto Ardon:
Combining Similarity and Adversarial Learning to Generate Visual Explanation: Application to Medical Image Classification. ICPR 2020: 7188-7195 - [c8]Elvire Roblin
, Paul-Henry Cournède
, Stefan Michiels
:
On the Use of Neural Networks with Censored Time-to-Event Data. ISMCO 2020: 56-67 - [i1]Martin Charachon, Céline Hudelot, Paul-Henry Cournède, Camille Ruppli, Roberto Ardon:
Combining Similarity and Adversarial Learning to Generate Visual Explanation: Application to Medical Image Classification. CoRR abs/2012.07332 (2020)
2010 – 2019
- 2019
- [j15]Charlotte Baey
, Paul-Henry Cournède
, Estelle Kuhn
:
Asymptotic distribution of likelihood ratio test statistics for variance components in nonlinear mixed effects models. Comput. Stat. Data Anal. 135: 107-122 (2019) - [c7]Mahmoud Bentriou, Paolo Ballarini
, Paul-Henry Cournède
:
Reachability Design Through Approximate Bayesian Computation. CMSB 2019: 207-223 - 2017
- [j14]Robert Beyer, Dominik Bayer
, Hans Pretzsch
, Paul-Henry Cournède
:
Reconstructing minimal length tree branch systems from leaf positions. Ecol. Informatics 42: 61-66 (2017) - 2016
- [j13]Konstantinos Koutroumpas, Paolo Ballarini
, Irene Votsi, Paul-Henry Cournède
:
Bayesian parameter estimation for the Wnt pathway: an infinite mixture models approach. Bioinform. 32(17): 781-789 (2016) - [c6]Chloé Adam, Antoine Aliotti, Paul-Henry Cournède
:
Learning from User Workflows for the Characterization and Prediction of Software Crashes. ICDM Workshops 2016: 1023-1030 - 2015
- [c5]Benoit Bayol, Yuting Chen, Charlotte Baey, Gautier Viaud, Paul-Henry Cournède:
WIP - Promoting good modeling practice with a domain-specific language and statistical algorithms designed for parallel computing. SpringSim (TMS-DEVS) 2015: 143-148 - [c4]Gautier Viaud, Yuting Chen, Benoit Bayol, Paul-Henry Cournède:
A comparison of a generic MCMC-based algorithm for Bayesian estimation in C++, R and Julia: application to plant growth modeling. SpringSim (ANSS) 2015: 194-201 - 2014
- [j12]Cedric Loi, Paul-Henry Cournède
, Jean Françon:
A Symbolic Method to Analyse Patterns in Plant Structure. Comb. Probab. Comput. 23(5): 842-860 (2014) - [j11]Samis Trevezas, Sonia Malefaki
, Paul-Henry Cournède
:
Parameter estimation via stochastic variants of the ECM algorithm with applications to plant growth modeling. Comput. Stat. Data Anal. 78: 82-99 (2014) - [j10]Corina Iovan, Paul-Henry Cournède
, Thomas Guyard, Benoit Bayol, Didier Boldo, Matthieu Cord:
Model-Based Analysis-Synthesis for Realistic Tree Reconstruction and Growth Simulation. IEEE Trans. Geosci. Remote. Sens. 52(2): 1438-1450 (2014) - 2013
- [j9]Katarína Smolenová, Winfried Kurth, Paul-Henry Cournède:
Parallel Graph Grammars with Instantiation Rules Allow Efficient Structural Factorization of Virtual Vegetation. Electron. Commun. Eur. Assoc. Softw. Sci. Technol. 61 (2013) - [c3]Jacques Ramanathan, Yuting Chen
, Paul-Henry Cournède:
Optimal Control of Crop Irrigation based on the Hamilton-Jacobi-Bellman Equation. SIAM Conf. on Control and its Applications 2013: 21-28 - [c2]Yuting Chen
, Samis Trevezas, Paul-Henry Cournède:
Iterative convolution particle filtering for nonlinear parameter estimation and data assimilation with application to crop yield prediction. SIAM Conf. on Control and its Applications 2013: 67-74 - [c1]Benoit Bayol, Yuting Chen
, Paul-Henry Cournède:
Towards an EDSL to Enhance Good Modelling Practice for Non-linear Stochastic Discrete Dynamical Models - Application to Plant Growth Models. SIMULTECH 2013: 132-138 - 2012
- [j8]Lin Wu, François-Xavier Le Dimet, Philippe de Reffye, Bao-Gang Hu
, Paul-Henry Cournède
, Meng-Zhen Kang:
An optimal control methodology for plant growth - Case study of a water supply problem of sunflower. Math. Comput. Simul. 82(5): 909-923 (2012) - [j7]Qiongli Wu
, Paul-Henry Cournède
, Amélie Mathieu:
An efficient computational method for global sensitivity analysis and its application to tree growth modelling. Reliab. Eng. Syst. Saf. 107: 35-43 (2012)
2000 – 2009
- 2008
- [j6]Shuang-Hong Yang, Bao-Gang Hu
, Paul-Henry Cournède
:
Structural identifiability of generalized constraint neural network models for nonlinear regression. Neurocomputing 72(1-3): 392-400 (2008) - [j5]Meng-Zhen Kang, Paul-Henry Cournède
, Philippe de Reffye, D. Auclair, Bao-Gang Hu
:
Analytical study of a stochastic plant growth model: Application to the GreenLab model. Math. Comput. Simul. 78(1): 57-75 (2008) - 2007
- [j4]Vincent Le Chevalier, Marc Jaeger, Xing Mei, Paul-Henry Cournède
:
Simulation and Visualisation of Functional Landscapes: Effects of the Water Resource Competition Between Plants. J. Comput. Sci. Technol. 22(6): 835-845 (2007) - 2006
- [j3]Amélie Rostand-Mathieu, Paul-Henry Cournède
, Philippe de Reffye:
A dynamical model of plant growth with full retroaction between organogenesis and photosynthesis. ARIMA J. 4: 7 (2006) - [j2]Paul-Henry Cournède
, Meng-Zhen Kang, Amélie Mathieu, Jean François Barczi, Hong-Pin Yan, Bao-Gang Hu
, Philippe de Reffye:
Structural Factorization of Plants to Compute Their Functional and Architectural Growth. Simul. 82(7): 427-438 (2006) - 2005
- [j1]Lin Wu, Philippe de Reffye, Bao-Gang Hu, François-Xavier Le Dimet, Paul-Henry Cournède
:
Un problème d'optimisation des apports en eau pour la croissance des plantes dans le modèle GreenLab. ARIMA J. 3: 9 (2005)
Coauthor Index
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last updated on 2024-08-23 19:22 CEST by the dblp team
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