Gallinari, Patrick

78 publications

NeurIPS 2025 ENMA: Tokenwise Autoregression for Continuous Neural PDE Operators Armand Kassaï Koupaï, Lise Le Boudec, Louis Serrano, Patrick Gallinari

ICLR 2025 Learning a Neural Solver for Parametric PDEs to Enhance Physics-Informed Methods Lise Le Boudec, Emmanuel de Bezenac, Louis Serrano, Ramon Daniel Regueiro-Espino, Yuan Yin, Patrick Gallinari

ICLR 2025 SCOPE: A Self-Supervised Framework for Improving Faithfulness in Conditional Text Generation Song Duong, Florian Le Bronnec, Alexandre Allauzen, Vincent Guigue, Alberto Lumbreras, Laure Soulier, Patrick Gallinari

ICML 2025 Zebra: In-Context Generative Pretraining for Solving Parametric PDEs Louis Serrano, Armand Kassaı̈ Koupaı̈, Thomas X Wang, Pierre Erbacher, Patrick Gallinari

NeurIPS 2024 AROMA: Preserving Spatial Structure for Latent PDE Modeling with Local Neural Fields Louis Serrano, Thomas X Wang, Etienne Le Naour, Jean-Noël Vittaut, Patrick Gallinari

ICMLW 2024 AROMA: Preserving Spatial Structure for Latent PDE Modeling with Local Neural Fields Louis Serrano, Thomas X Wang, Etienne Le Naour, Jean-Noël Vittaut, Patrick Gallinari

ICLRW 2024 AutoBasisEncoder: Pre-Trained Neural Field Basis via Autoencoding for Operator Learning Thomas X Wang, Nicolas Baskiotis, Patrick Gallinari

NeurIPS 2024 Boosting Generalization in Parametric PDE Neural Solvers Through Adaptive Conditioning Armand Kassaï Koupaï, Jorge Mifsut Benet, Yuan Yin, Jean-Noël Vittaut, Patrick Gallinari

ICLRW 2024 Latent Diffusion Transformer with Local Neural Field as PDE Surrogate Model Louis Serrano, Jean-Noël Vittaut, Patrick Gallinari

ICLRW 2024 Learn to Adapt Parametric Solvers Under Incomplete Physics Armand Kassaï Koupaï, Yuan Yin, Patrick Gallinari

ICLRW 2024 Learning Iterative Algorithms to Solve PDEs. Lise Le Boudec, Emmanuel de Bezenac, Louis Serrano, Yuan Yin, Patrick Gallinari

TMLR 2024 Time Series Continuous Modeling for Imputation and Forecasting with Implicit Neural Representations Etienne Le Naour, Louis Serrano, Léon Migus, Yuan Yin, Ghislain Agoua, Nicolas Baskiotis, Patrick Gallinari, Vincent Guigue

ICLRW 2024 Zebra: A Continuous Generative Transformer for Solving Parametric PDEs Louis Serrano, Pierre Erbacher, Jean-Noël Vittaut, Patrick Gallinari

ECML-PKDD 2023 Adversarial Sample Detection Through Neural Network Transport Dynamics Skander Karkar, Patrick Gallinari, Alain Rakotomamonjy

ICLR 2023 Continuous PDE Dynamics Forecasting with Implicit Neural Representations Yuan Yin, Matthieu Kirchmeyer, Jean-Yves Franceschi, Alain Rakotomamonjy, Patrick Gallinari

ICMLW 2023 Deep Learning Approach for Cardiac Electrophysiology Model Correction Victoriya Kashtanova, Mihaela Pop, Patrick Gallinari, Maxime Sermesant

MIDL 2023 Deep Learning for Model Correction in Cardiac Electrophysiological Imaging Victoriya Kashtanova, Ibrahim Ayed, Andony Arrieula, Mark Potse, Patrick Gallinari, Maxime Sermesant

ICMLW 2023 INFINITY: Neural Field Modeling for Reynolds-Averaged Navier-Stokes Equations Louis Serrano, Léon Migus, Yuan Yin, Jocelyn Ahmed Mazari, Jean-Noël Vittaut, Patrick Gallinari

AISTATS 2023 Learning from Multiple Sources for Data-to-Text and Text-to-Data Song Duong, Alberto Lumbreras, Mike Gartrell, Patrick Gallinari

NeurIPS 2023 Module-Wise Training of Neural Networks via the Minimizing Movement Scheme Skander Karkar, Ibrahim Ayed, Emmanuel de Bézenac, Patrick Gallinari

ICLRW 2023 Operator Learning on Free-Form Geometries Louis Serrano, Jean-Noël Vittaut, Patrick Gallinari

NeurIPS 2023 Operator Learning with Neural Fields: Tackling PDEs on General Geometries Louis Serrano, Lise Le Boudec, Armand Kassaï Koupaï, Thomas X Wang, Yuan Yin, Jean-Noël Vittaut, Patrick Gallinari

ICMLW 2023 Physics-Based Deep Learning Framework to Learn and Forecast Cardiac Electrophysiology Dynamics Victoriya Kashtanova, Maxime Sermesant, Patrick Gallinari

ICLRW 2023 Stability of Implicit Neural Networks for Long-Term Forecasting in Dynamical Systems Léon Migus, Julien Salomon, Patrick Gallinari

ICML 2022 A Neural Tangent Kernel Perspective of GANs Jean-Yves Franceschi, Emmanuel De Bézenac, Ibrahim Ayed, Mickael Chen, Sylvain Lamprier, Patrick Gallinari

NeurIPS 2022 AirfRANS: High Fidelity Computational Fluid Dynamics Dataset for Approximating Reynolds-Averaged Navier–Stokes Solutions Florent Bonnet, Jocelyn Mazari, Paola Cinnella, Patrick Gallinari

ICLRW 2022 An Extensible Benchmarking Graph-Mesh Dataset for Studying Steady-State Incompressible Navier-Stokes Equations Florent Bonnet, Jocelyn Ahmed Mazari, Thibaut Munzer, Pierre Yser, Patrick Gallinari

ICLR 2022 Constrained Physical-Statistics Models for Dynamical System Identification and Prediction Jérémie Dona, Marie Déchelle, Patrick Gallinari, Marina Levy

NeurIPSW 2022 Continuous PDE Dynamics Forecasting with Implicit Neural Representations Yuan Yin, Matthieu Kirchmeyer, Jean-Yves Franceschi, Alain Rakotomamonjy, Patrick Gallinari

NeurIPS 2022 Diverse Weight Averaging for Out-of-Distribution Generalization Alexandre Rame, Matthieu Kirchmeyer, Thibaud Rahier, Alain Rakotomamonjy, Patrick Gallinari, Matthieu Cord

ICML 2022 Generalizing to New Physical Systems via Context-Informed Dynamics Model Matthieu Kirchmeyer, Yuan Yin, Jeremie Dona, Nicolas Baskiotis, Alain Rakotomamonjy, Patrick Gallinari

ICLR 2022 Mapping Conditional Distributions for Domain Adaptation Under Generalized Target Shift Matthieu Kirchmeyer, Alain Rakotomamonjy, Emmanuel de Bezenac, Patrick Gallinari

MLJ 2022 Modelling Spatiotemporal Dynamics from Earth Observation Data with Neural Differential Equations Ibrahim Ayed, Emmanuel de Bézenac, Arthur Pajot, Patrick Gallinari

ICLRW 2022 Multi-Scale Physical Representations for Approximating PDE Solutions with Graph Neural Operators Léon Migus, Yuan Yin, Jocelyn Ahmed Mazari, Patrick Gallinari

ICLR 2021 Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting Yuan Yin, Vincent Le Guen, Jérémie Dona, Emmanuel de Bezenac, Ibrahim Ayed, Nicolas Thome, Patrick Gallinari

ECML-PKDD 2021 CycleGAN Through the Lens of (Dynamical) Optimal Transport Emmanuel de Bézenac, Ibrahim Ayed, Patrick Gallinari

ECML-PKDD 2021 Differentiable Feature Selection, a Reparameterization Approach Jérémie Donà, Patrick Gallinari

NeurIPS 2021 LEADS: Learning Dynamical Systems That Generalize Across Environments Yuan Yin, Ibrahim Ayed, Emmanuel de Bézenac, Nicolas Baskiotis, Patrick Gallinari

ICLR 2021 PDE-Driven Spatiotemporal Disentanglement Jérémie Donà, Jean-Yves Franceschi, Sylvain Lamprier, Patrick Gallinari

ECML-PKDD 2020 A Principle of Least Action for the Training of Neural Networks Skander Karkar, Ibrahim Ayed, Emmanuel de Bézenac, Patrick Gallinari

NeurIPS 2020 Normalizing Kalman Filters for Multivariate Time Series Analysis Emmanuel de Bézenac, Syama Sundar Rangapuram, Konstantinos Benidis, Michael Bohlke-Schneider, Richard Kurle, Lorenzo Stella, Hilaf Hasson, Patrick Gallinari, Tim Januschowski

ICML 2020 Stochastic Latent Residual Video Prediction Jean-Yves Franceschi, Edouard Delasalles, Mickael Chen, Sylvain Lamprier, Patrick Gallinari

ICML 2019 Context-Aware Zero-Shot Learning for Object Recognition Eloi Zablocki, Patrick Bordes, Laure Soulier, Benjamin Piwowarski, Patrick Gallinari

ECML-PKDD 2019 Copy Mechanism and Tailored Training for Character-Based Data-to-Text Generation Marco Roberti, Giovanni Bonetta, Rossella Cancelliere, Patrick Gallinari

ICLR 2019 Unsupervised Adversarial Image Reconstruction Arthur Pajot, Emmanuel de Bezenac, Patrick Gallinari

MLJ 2018 A Distributed Frank-Wolfe Framework for Learning Low-Rank Matrices with the Trace Norm Wenjie Zheng, Aurélien Bellet, Patrick Gallinari

ICLR 2018 Deep Learning for Physical Processes: Incorporating Prior Scientific Knowledge Emmanuel de Bezenac, Arthur Pajot, Patrick Gallinari

AAAI 2018 Learning Multi-Modal Word Representation Grounded in Visual Context Eloi Zablocki, Benjamin Piwowarski, Laure Soulier, Patrick Gallinari

JMLR 2018 Profile-Based Bandit with Unknown Profiles Sylvain Lamprier, Thibault Gisselbrecht, Patrick Gallinari

ECML-PKDD 2018 Time Warp Invariant Dictionary Learning for Time Series Clustering: Application to Music Data Stream Analysis Saeed Varasteh Yazdi, Ahlame Douzal Chouakria, Patrick Gallinari, Manuel Moussallam

ECML-PKDD 2017 Variational Thompson Sampling for Relational Recurrent Bandits Sylvain Lamprier, Thibault Gisselbrecht, Patrick Gallinari

ECML-PKDD 2016 Learning Distributed Representations of Users for Source Detection in Online Social Networks Simon Bourigault, Sylvain Lamprier, Patrick Gallinari

ECML-PKDD 2016 Linear Bandits in Unknown Environments Thibault Gisselbrecht, Sylvain Lamprier, Patrick Gallinari

ECML-PKDD 2016 Multilabel Classification on Heterogeneous Graphs with Gaussian Embeddings Ludovic Dos Santos, Benjamin Piwowarski, Patrick Gallinari

ICLR 2014 Learning Information Spread in Content Networks Cédric Lagnier, Simon Bourigault, Sylvain Lamprier, Ludovic Denoyer, Patrick Gallinari

ICLR 2014 Learning States Representations in POMDP Gabriella Contardo, Ludovic Denoyer, Thierry Artières, Patrick Gallinari

ICLR 2014 Sequentially Generated Instance-Dependent Image Representations for Classification Gabriel Dulac-Arnold, Ludovic Denoyer, Nicolas Thome, Matthieu Cord, Patrick Gallinari

MLJ 2013 Calibration and Regret Bounds for Order-Preserving Surrogate Losses in Learning to Rank Clément Calauzènes, Nicolas Usunier, Patrick Gallinari

ECML-PKDD 2013 Cross-Domain Recommendation via Cluster-Level Latent Factor Model Sheng Gao, Hao Luo, Da Chen, Shantao Li, Patrick Gallinari, Jun Guo

NeurIPS 2013 Robust Bloom Filters for Large MultiLabel Classification Tasks Moustapha M Cisse, Nicolas Usunier, Thierry Artières, Patrick Gallinari

ECML-PKDD 2012 Fast Reinforcement Learning with Large Action Sets Using Error-Correcting Output Codes for MDP Factorization Gabriel Dulac-Arnold, Ludovic Denoyer, Philippe Preux, Patrick Gallinari

ECML-PKDD 2012 Learning Compact Class Codes for Fast Inference in Large Multi Class Classification Moustapha Cissé, Thierry Artières, Patrick Gallinari

NeurIPS 2012 On the (Non-)existence of Convex, Calibrated Surrogate Losses for Ranking Clément Calauzènes, Nicolas Usunier, Patrick Gallinari

MLJ 2012 Sequential Approaches for Learning Datum-Wise Sparse Representations Gabriel Dulac-Arnold, Ludovic Denoyer, Philippe Preux, Patrick Gallinari

ECML-PKDD 2011 Datum-Wise Classification: A Sequential Approach to Sparsity Gabriel Dulac-Arnold, Ludovic Denoyer, Philippe Preux, Patrick Gallinari

ICML 2011 Learning Scoring Functions with Order-Preserving Losses and Standardized Supervision David Buffoni, Clément Calauzènes, Patrick Gallinari, Nicolas Usunier

JMLR 2010 Erratum: SGDQN Is Less Careful than Expected Antoine Bordes, Léon Bottou, Patrick Gallinari, Jonathan Chang, S. Alex Smith

ICML 2009 Ranking with Ordered Weighted Pairwise Classification Nicolas Usunier, David Buffoni, Patrick Gallinari

JMLR 2009 SGD-QN: Careful Quasi-Newton Stochastic Gradient Descent Antoine Bordes, Léon Bottou, Patrick Gallinari

ECML-PKDD 2009 Simulated Iterative Classification a New Learning Procedure for Graph Labeling Francis Maes, Stéphane Peters, Ludovic Denoyer, Patrick Gallinari

MLJ 2009 Structured Prediction with Reinforcement Learning Francis Maes, Ludovic Denoyer, Patrick Gallinari

ICML 2007 Solving Multiclass Support Vector Machines with LaRank Antoine Bordes, Léon Bottou, Patrick Gallinari, Jason Weston

ECML-PKDD 2006 A Selective Sampling Strategy for Label Ranking Massih-Reza Amini, Nicolas Usunier, François Laviolette, Alexandre Lacasse, Patrick Gallinari

IJCAI 2005 Automatic Learning of Domain Model for Personalized Hypermedia Applications Hermine Njike Fotzo, Thierry Artières, Patrick Gallinari, Julien Blanchard, Guillaume Letellier

NeurIPS 2005 Generalization Error Bounds for Classifiers Trained with Interdependent Data Nicolas Usunier, Massih R. Amini, Patrick Gallinari

IJCAI 2003 Semi-Supervised Learning with Explicit Misclassification Modeling Massih-Reza Amini, Patrick Gallinari

ECML-PKDD 2002 Learning Classification with Both Labeled and Unlabeled Data Jean-Noël Vittaut, Massih-Reza Amini, Patrick Gallinari

NeurIPS 1990 A Framework for the Cooperation of Learning Algorithms Léon Bottou, Patrick Gallinari