Pré-publication, Document de travail
Machine Learning
Affichage des résultats 1 à 12 sur 65 au total
Machine Learning : 1 à 12 sur 65 au total
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Communication dans un congrès
Hui Yang, Mostepha Khouadjia, Nacéra Bennacer Seghouani, Yue Ma, Serge Delmas. Explainable Action-Recognition Based Approach For Unsupervised Video Anomaly Detection. International Symposium on Visual Computing (ISVC), Oct 2024, Lake Tahoe, United States. ⟨hal-04755410⟩
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Communication dans un congrès
Audrey Poinsot, Alessandro Leite, Nicolas Chesneau, Michele Sebag, Marc Schoenauer. Learning Structural Causal Models through Deep Generative Models: Methods, Guarantees, and Challenges. IJCAI 2024 - Thirty-Third International Joint Conference on Artificial Intelligence, Aug 2024, Jeju, South Korea. pp.8207-8215, ⟨10.24963/ijcai.2024/907⟩. ⟨hal-04706985⟩
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Communication dans un congrès
Xiaoxi Wei, A. Aldo Faisal, Moritz Grosse-Wentrup, Sylvain Chevallier, Vinay Jayaram, et al.. 2021 BEETL Competition: Advancing Transfer Learning for Subject Independence & Heterogenous EEG Data Sets. NeurIPS, Nov 2022, Nouvelle Orleans, United States. ⟨hal-04677636⟩
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Thèse
Emmanuel Menier. Deep Learning for Reduced Order Modeling. Machine Learning [cs.LG]. Université Paris-Saclay, 2024. English. ⟨NNT : 2024UPASG004⟩. ⟨tel-04616516⟩
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Communication dans un congrès
Paulo Henrique Couto, Quang Phuoc Ho, Nageeta Kumari, Benedictus Kent Rachmat, Thanh Gia Hieu Khuong, et al.. RelevAI-Reviewer: A Benchmark on AI Reviewers for Survey Paper Relevance. CAp 2024 - Conférence sur l'Apprentissage Automatique, Jul 2024, Lille, France. ⟨hal-04608255⟩
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HDR
Paola Tubaro. Décrypter la société des plateformes : Organisations, marchés et réseaux dans l'économie numérique. Sociology. Institut d'Etudes Politiques de Paris, 2019. ⟨tel-04547405⟩
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Article dans une revue
Sibo Cheng, César Quilodrán-Casas, Said Ouala, Alban Farchi, Che Liu, et al.. Machine learning with data assimilation and uncertainty quantification for dynamical systems: a review. IEEE/CAA Journal of Automatica Sinica, 2023, 10 (6), pp.1361-1387. ⟨10.1109/JAS.2023.123537⟩. ⟨hal-04039094⟩
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Pré-publication, Document de travail
Rahul Sundar, Didier Lucor, Sunetra Sarkar. Understanding the training of PINNs for unsteady flow past a plunging foil through the lens of input subdomain level loss function gradients. 2024. ⟨hal-04481710⟩
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Thèse
Jérémy Guez. Cultural transmission of reproductive success: Causal mechanisms, genetic consequences, and machine-learning-based inference. Populations and Evolution [q-bio.PE]. Muséum national d'histoire naturelle, 2023. English. ⟨NNT : ⟩. ⟨tel-04482448⟩
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Communication dans un congrès
Ludovic Coelho, Nicolò Fabbiane, Christian Fagiano, Cédric Julien, Didier Lucor. Gradient reliability-based design optimization of a composite plate through multi-scale design spaces. International Forum on Aeroelasticity and Structural Dynamics IFASD 2022, Jun 2022, Madrid, Spain. pp.2563-2579. ⟨hal-04463058⟩
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Communication dans un congrès
Benoît Choffin, Naonori Ueda. Scaling Bayesian Optimization up to Higher Dimensions: a Review and Comparison of Recent Algorithms. 2018 IEEE 28th International Workshop on Machine Learning for Signal Processing (MLSP), Sep 2018, Aalborg, Denmark. ⟨10.1109/MLSP.2018.8517011⟩. ⟨hal-02265260⟩