Home » Teams » MLIA » Patrick Gallinari

Publications

  • Jean-Yves Franceschi, Emmanuel de Bézenac, Ibrahim Ayed, Mickaël Chen, Sylvain Lamprier, et al.. A Neural Tangent Kernel Perspective of GANs. Thirty-ninth International Conference on Machine Learning, Jul 2022, Baltimore, MD, United States. ⟨hal-03716574⟩
  • Florent Bonnet, Jocelyn Ahmed Mazari, Thibaut Munzer, Pierre Yser, Patrick Gallinari. AN EXTENSIBLE BENCHMARKING GRAPH-MESH DATASET FOR STUDYING STEADY-STATE INCOM-PRESSIBLE NAVIER-STOKES EQUATIONS. ICLR 2022 Workshop on Geometrical and Topological Representation Learning, Apr 2022, In remote, France. ⟨hal-03709263⟩
  • Leon Migus, Yuan Yin, Jocelyn Ahmed Mazari, Patrick Gallinari. MULTI-SCALE PHYSICAL REPRESENTATIONS FOR AP-PROXIMATING PDE SOLUTIONS WITH GRAPH NEU-RAL OPERATORS. ICLR 2022 Workshop on Geometrical and Topological Representation Learning, Apr 2022, En ligne, France. ⟨hal-03709247⟩
  • Matthieu Kirchmeyer, Alain Rakotomamonjy, Emmanuel de Bezenac, Patrick Gallinari. Mapping conditional distributions for domain adaptation under generalized target shift. International Conference on Learning Representations, Apr 2022, Virtual, Unknown Region. ⟨hal-03396183v2⟩
  • Jean-Yves Franceschi, Emmanuel de Bézenac, Ibrahim Ayed, Mickaël Chen, Sylvain Lamprier, et al.. A Neural Tangent Kernel Perspective of GANs. Thirty-ninth International Conference on Machine Learning, International Machine Learning Society, Jul 2022, Baltimore, MD, United States. pp.6660--6704. ⟨hal-03254591v4⟩
  • Yuan Yin, Ibrahim Ayed, Emmanuel de Bézenac, Nicolas Baskiotis, Patrick Gallinari. LEADS: Learning Dynamical Systems that Generalize Across Environments. The Thirty-Fifth Annual Conference on Neural Information Processing Systems (NeurIPS 2021), Dec 2021, Online, Unknown Region. ⟨hal-03261055v2⟩
  • Yuan Yin, Vincent Le Guen, Jérémie Donà, Emmanuel de Bézenac, Ibrahim Ayed, et al.. Augmenting physical models with deep networks for complex dynamics forecasting. Journal of Statistical Mechanics: Theory and Experiment, IOP Publishing, 2021, 2021 (12), pp.124012. ⟨10.1088/1742-5468/ac3ae5⟩. ⟨hal-03508401v2⟩
  • Clément Rebuffel, Thomas Scialom, Laure Soulier, Benjamin Piwowarski, Sylvain Lamprier, et al.. Data-QuestEval: A Reference-less Metric for Data-to-Text Semantic Evaluation. Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP), Nov 2021, Punta Cana, Dominican Republic. ⟨hal-03479905⟩
  • Bruno Taillé, Vincent Guigue, Geoffrey Scoutheeten, Patrick Gallinari. Separating Retention from Extraction in the Evaluation of End-to-end Relation Extraction. EMNLP 2021, Nov 2021, Punta Cana (online), Dominican Republic. pp.10438-10449. ⟨hal-03480371⟩
  • Matthieu Kirchmeyer, Patrick Gallinari, Alain Rakotomamonjy, Amin Mantrach. Unsupervised domain adaptation with non-stochastic missing data. Data Mining and Knowledge Discovery, Springer, 2021, 35 (6), pp.2714-2755. ⟨10.1007/s10618-021-00775-3⟩. ⟨hal-03338879v2⟩
  • Clément Rebuffel, Marco Roberti, Laure Soulier, Geoffrey Scoutheeten, Rossella Cancelliere, et al.. Controlling hallucinations at word level in data-to-text generation. Data Mining and Knowledge Discovery, Springer, 2021, ⟨10.1007/s10618-021-00801-4⟩. ⟨hal-03479792⟩
  • Victoriya Kashtanova, Ibrahim Ayed, Nicolas Cedilnik, Patrick Gallinari, Maxime Sermesant. EP-Net 2.0: Out-of-Domain Generalisation for Deep Learning Models of Cardiac Electrophysiology. FIMH 2021 - 11th International Conference on Functional Imaging and Modeling of the Heart, Jun 2021, Stanford, CA (virtual), United States. pp.482-492, ⟨10.1007/978-3-030-78710-3_46⟩. ⟨hal-03369201⟩
  • Jérémie Donà, Jean-Yves Franceschi, Sylvain Lamprier, Patrick Gallinari. PDE-Driven Spatiotemporal Disentanglement. The Ninth International Conference on Learning Representations, International Conference on Representation Learning, May 2021, Vienne, Austria. ⟨hal-02911067v3⟩
  • Jérémie Donà, Jean-Yves Franceschi, Sylvain Lamprier, Patrick Gallinari. PDE-Driven Spatiotemporal Disentanglement. The Ninth International Conference on Learning Representations, May 2021, Vienne (virtual), Austria. ⟨hal-03181039⟩
  • Giovanni Bonetta, Marco Roberti, Rossella Cancelliere, Patrick Gallinari. The Rare Word Issue in Natural Language Generation: A Character-Based Solution. Informatics, MDPI, 2021, 8 (1), pp.20. ⟨10.3390/informatics8010020⟩. ⟨hal-03184301⟩
  • Jérémie Dona, Patrick Gallinari. Differentiable Feature Selection, a Reparameterization Approach. ECML PDKK 2021, Sep 2021, Virtual, France. ⟨hal-03291389⟩
  • Yuan Yin, Vincent Le Guen, Jérémie Dona, Ibrahim Ayed, Emmanuel de Bézenac, et al.. Augmenting physical models with deep networks for complex dynamics forecasting. Ninth International Conference on Learning Representations ICLR 2021, 2021, Vienna (virtual), Austria. ⟨hal-03137025⟩
  • Clément Rebuffel, Laure Soulier, Geoffrey Scoutheeten, Patrick Gallinari. PARENTing via Model-Agnostic Reinforcement Learning to Correct Pathological Behaviors in Data-to-Text Generation. Proceedings of the 13th International Conference on Natural Language Generation, INLG 2020, Dec 2020, Dublin, Ireland. ⟨hal-03479883⟩
  • Bruno Taillé, Vincent Guigue, Geoffrey Scoutheeten, Patrick Gallinari. Let’s Stop Incorrect Comparisons in End-to-end Relation Extraction!. Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), Nov 2020, Punta Cana (Online), Dominican Republic. pp.3689-3701, ⟨10.18653/v1/2020.emnlp-main.301⟩. ⟨hal-03480380⟩
  • Skander Karkar, Ibrahim Ayed, Emmanuel de Bezenac, Patrick Gallinari. A Principle of Least Action for the Training of Neural Networks. ECML PKDD, Sep 2020, Ghent, Belgium. ⟨hal-03038615⟩
  • Thi Phuong Thao Tran, Ahlame Douzal-Chouakria, Saeed Varasteh Yazdi, Paul Honeine, Patrick Gallinari. Interpretable time series kernel analytics by pre-image estimation. Artificial Intelligence, Elsevier, 2020, 286, pp.103342. ⟨10.1016/j.artint.2020.103342⟩. ⟨hal-03088295⟩
  • Clément Rebuffel, Laure Soulier, Geoffrey Scoutheeten, Patrick Gallinari. Capturing Entity Hierarchy in Data-to-Text Generative Models. First Joint Conference of the Information Retrieval Communities in Europe (CIRCLE 2020), Jul 2020, Online, France. ⟨hal-03479813⟩
  • Evangelos Moschos, Alexandre Stegner, Olivier Schwander, Patrick Gallinari. Classification of Eddy Sea Surface Temperature Signatures Under Cloud Coverage. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, IEEE, 2020, 13, pp.3437-3447. ⟨10.1109/JSTARS.2020.3001830⟩. ⟨hal-03028674⟩
  • Evangelos Moschos, Olivier Schwander, Alexandre Stegner, Patrick Gallinari. DEEP-SST-EDDIES: A Deep Learning framework to detect oceanic eddies in Sea Surface Temperature images. ICASSP 2020 - 45th International Conference on Acoustics, Speech, and Signal Processing, May 2020, Barcelona, Spain. ⟨hal-02470051⟩
  • Clément Rebuffel, Laure Soulier, Geoffrey Scoutheeten, Patrick Gallinari. A Hierarchical Model for Data-to-Text Generation. 42nd European Conference on IR Research, ECIR 2020, Apr 2020, Lisbon, Portugal. pp.65-80, ⟨10.1007/978-3-030-45439-5_5⟩. ⟨hal-02774325⟩
  • Karan Aggarwal, Matthieu Kirchmeyer, Pranjul Yadav, S. Sathiya Keerthi, Patrick Gallinari. Benchmarking Regression Methods: A comparison with CGAN. 2020. ⟨hal-02457453⟩
  • Bruno Taille, Vincent Guigue, Patrick Gallinari. Contextualized Embeddings in Named-Entity Recognition: An Empirical Study on Generalization. ECIR 2020 - 42nd European Conference on Information Retrieval, Apr 2020, Lisbon, Portugal. ⟨hal-02503463⟩
  • Jean-Yves Franceschi, Edouard Delasalles, Mickaël Chen, Sylvain Lamprier, Patrick Gallinari. Stochastic Latent Residual Video Prediction. Thirty-seventh International Conference on Machine Learning, International Machine Learning Society, Jul 2020, Vienne, Austria. pp.3233--3246. ⟨hal-02484182v4⟩
  • Clara Gainon de Forsan de Gabriac, Vincent Guigue, Patrick Gallinari. Resume: A Robust Framework for Professional Profile Learning & Evaluation. ESANN 2020 - 28th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, Apr 2020, Bruges, Belgium. ⟨hal-02503464⟩
  • Emmanuel de Bezenac, Arthur Pajot, Patrick Gallinari. Deep Learning for Physical Processes: Incorporating Prior Scientific Knowledge. 2019. ⟨hal-02418362⟩
  • Ibrahim Ayed, Emmanuel de Bézenac, Arthur Pajot, Julien Brajard, Patrick Gallinari. Learning Dynamical Systems from Partial Observations. 2019. ⟨hal-02418376⟩
  • Edouard Delasalles, Ali Ziat, Ludovic Denoyer, Patrick Gallinari. Spatio-temporal neural networks for space-time data modeling and relation discovery. Knowledge and Information Systems (KAIS), Springer, 2019, 61 (3), pp.1241-1267. ⟨10.1007/s10115-018-1291-x⟩. ⟨hal-02336358⟩
  • Yu Zhao, Huali Feng, Patrick Gallinari. Embedding Learning with Triple Trustiness on Noisy Knowledge Graph. Entropy, MDPI, 2019, 21 (11), pp.1083. ⟨10.3390/e21111083⟩. ⟨hal-02430754⟩
  • Patrick Bordes, Éloi Zablocki, Laure Soulier, Benjamin Piwowarski, Patrick Gallinari. Incorporating Visual Semantics into Sentence Representations within a Grounded Space. 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing, Nov 2019, Hong Kong, China. pp.696-707, ⟨10.18653/v1/D19-1064⟩. ⟨hal-02351003⟩
  • Sylvain Lamprier, Thibault Gisselbrecht, Patrick Gallinari. Contextual Bandits with Hidden Contexts: a Focused Data Capture From Social Media Streams. Data Mining and Knowledge Discovery, Springer, 2019, 33, pp.1853-1893. ⟨10.1007/s10618-019-00648-w⟩. ⟨hal-02505162⟩
  • Eloi Zablocki, Patrick Bordes, Benjamin Piwowarski, Laure Soulier, Patrick Gallinari. Context-Aware Zero-Shot Learning for Object Recognition. Thirty-sixth International Conference on Machine Learning (ICML), Jun 2019, Long Beach, CA, United States. ⟨hal-02116654⟩
  • Ibrahim Ayed, Nicolas Cedilnik, Patrick Gallinari, Maxime Sermesant. EP-Net: Learning Cardiac Electrophysiology Models for Physiology-based Constraints in Data-Driven Predictions. FIMH 2019 - 10th International Conference on Functional Imaging of the Hearth, Jun 2019, Bordeaux, France. pp.55-63. ⟨hal-02106618⟩
  • Charles-Emmanuel Dias, Vincent Guigue, Patrick Gallinari. Filtrage collaboratif explicite par analyse de sentiments à l’aveugle. CAp 2019 - 21ème Conférence sur l'Apprentissage automatique, Jul 2019, Toulouse, France. ⟨hal-02503467⟩
  • Bruno Taillé, Vincent Guigue, Patrick Gallinari. Contextualized Embeddings in Named-Entity Recognition: An Empirical Study on Generalization. EurNLP, Oct 2019, London, United Kingdom. ⟨hal-02503466⟩
  • Bruno Taillé, Vincent Guigue, Patrick Gallinari. Une Etude Empirique de la Capacité de Généralisation des Plongements de Mots Contextuels en Extraction d'Entités. CAp 2019 - 21ème Conférence sur l'Apprentissage automatique, Jul 2019, Toulouse, France. ⟨hal-02503468⟩
  • Charles-Emmanuel Dias, Clara Gainon de Forsan De Gabriac, Vincent Guigue, Patrick Gallinari. RNN & modèle d’attention pour l’apprentissage de profils textuels personnalisés. Document Numérique, Lavoisier, 2019, 22 (3), pp.9-27. ⟨10.3166/dn.22.3.9-27⟩. ⟨hal-02503470⟩
  • Saeed Varasteh Yazdi, Ahlame Douzal-Chouakria, Patrick Gallinari, Manuel Moussallam. Time warp invariant dictionary learning for time series clustering: application to music data stream analysis. ECML/PKDD, 2018, Sep 2018, Dublin, Ireland. ⟨hal-01898905⟩
  • Ludovic dos Santos, Benjamin Piwowarski, Ludovic Denoyer, Patrick Gallinari. Representation Learning for Classification in Heterogeneous Graphs with Application to Social Networks. ACM Transactions on Knowledge Discovery from Data (TKDD), ACM, 2018, 12 (5), pp.1 - 33. ⟨10.1145/3201603⟩. ⟨hal-01853928⟩
  • Emeric Tonnelier, Nicolas Baskiotis, Vincent Guigue, Patrick Gallinari. Anomaly detection in smart card logs and distant evaluation with Twitter: a robust framework. Neurocomputing, Elsevier, 2018, 298, pp.109-121. ⟨10.1016/j.neucom.2017.12.067⟩. ⟨hal-02503474⟩
  • Eloi Zablocki, Benjamin Piwowarski, Laure Soulier, Patrick Gallinari. Apprentissage multimodal de représentation de mots à l'aide de contexte visuel. Conférence sur l'Apprentissage Automatique, Jun 2018, Rouen, France. ⟨hal-01842358⟩
  • Hadrien Titeux, Benjamin Piwowarski, Patrick Gallinari. Représentations Gaussiennes pour le Filtrage Collaboratif. 15ème COnférence en Recherche d'Informations et Applications - CORIA 2018, May 2018, Rennes, France. ⟨10.24348/coria.2018.paper31⟩. ⟨hal-02074930⟩
  • Alejandro Lopez-Rincon, Alberto Tonda, Mohamed Elati, Olivier Schwander, Benjamin Piwowarski, et al.. Evolutionary optimization of convolutional neural networks for cancer miRNA biomarkers classification. Applied Soft Computing, Elsevier, 2018, 65, pp.91 - 100. ⟨10.1016/j.asoc.2017.12.036⟩. ⟨hal-01700622⟩
  • Éloi Zablocki, Benjamin Piwowarski, Laure Soulier, Patrick Gallinari. Learning Multi-Modal Word Representation Grounded in Visual Context. Association for the Advancement of Artificial Intelligence (AAAI), Feb 2018, New Orleans, United States. ⟨hal-01632414⟩
  • Charles-Emmanuel Dias, Vincent Guigue, Patrick Gallinari. Regularize and Explicit Collaborative Filtering With Textual Attention. ESANN 2018 - European Symposium on Artificial Neural Networks, Apr 2018, Bruges, Belgium. ⟨hal-02503475⟩
  • Wenjie Zheng, Aurélien Bellet, Patrick Gallinari. A Distributed Frank-Wolfe Framework for Learning Low-Rank Matrices with the Trace Norm. Machine Learning, Springer Verlag, 2018, ⟨10.1007/s10994-018-5713-5⟩. ⟨hal-01922994⟩