المؤلفون: Masias Bruns, Mireia

المساهمون: University/Department: Universitat Pompeu Fabra. Departament de Tecnologies de la Informació i les Comunicacions

Thesis Advisors: Piella, Gemma, González Ballester, Miguel Ángel

المصدر: TDX (Tesis Doctorals en Xarxa)

مصطلحات موضوعية: Psychotic disorders, Normalizing flows, Normative modeling, Optimal transport, Whole-brain models, Amortized inverse-inference, Trastorns psicòtics, Fluxos normalitzadors, Modelització normativa, Transport òptim, Models de funció cerebral, Inferència inversa amortitzada

وصف الملف: application/pdf

URL الوصول: http://hdl.handle.net/10803/691941

المؤلفون: Halin, Anaïs, Pierard, Sébastien, Vandeghen, Renaud, Gérin, Benoît, Zanella, Maxime, Colot, Martin, Held, Jan, Cioppa, Anthony, Jean, Emmanuel, Bontempi, Gianluca, Mahmoudi, Saïd, Macq, Benoît, Van Droogenbroeck, Marc

المصدر: First International Workshop on AI-based All-Weather Surveillance System (AWSS), Hanoï, Vietnam [VN], 9 décembre 2024

مصطلحات موضوعية: Domain Characterization, Domain Adaptation, Normalizing Flows, Autonomous Vehicles, Weather Prediction, Engineering, computing & technology, Electrical & electronics engineering, Ingénierie, informatique & technologie, Ingénierie électrique & électronique

URL الوصول: https://orbi.uliege.be/handle/2268/326995

المؤلفون: Grumitt, Richard DP, Karamanis, Minas, Seljak, Uroš

المصدر: Inverse Problems. 40(12)

مصطلحات موضوعية: Applied Mathematics, Pure Mathematics, Mathematical Sciences, Generic health relevance, inverse problems, Bayesian inference, ensemble Kalman inversion, sequential Monte Carlo, normalizing flows, Mathematical Physics, Applied mathematics, Pure mathematics

وصف الملف: application/pdf

URL الوصول: https://escholarship.org/uc/item/8ph0t1q7
https://escholarship.org/content/qt8ph0t1q7/qt8ph0t1q7.pdf

المؤلفون: Johansson, Edvin, Sönnergaard, Matilda, Selpi, Selpi, 1977, Rahrovani, Sadegh, Basimfar, Parsia

المصدر: 26th IEEE International Conference on Intelligent Transportation Systems, ITSC 2023, Bilbao, Spain IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC. :1375-1380

مصطلحات موضوعية: NURBS, risk analysis of autonomous vehicles, generative models, statistical scenario model, cut-in traffic scenario, trajectory generation, normalizing flows

وصف الملف: electronic

URL الوصول: https://research.chalmers.se/publication/539209
https://research.chalmers.se/publication/540320
https://research.chalmers.se/publication/540320/file/540320_Fulltext.pdf

المؤلفون: Ialongo, Alessandro Davide

المساهمون: Rasmussen, Carl Edward

مصطلحات موضوعية: Variational Inference, Gaussian Processes, State Space Models, Dynamical Systems, Machine Learning, Bayesian Methods, Statistical Inference, Normalizing Flows, Gaussian Process State Space Model

URL الوصول: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.871667

المؤلفون: Wehenkel, Antoine, Louppe, Gilles

المصدر: ICML Workshop on Invertible Neural Networks, Normalizing Flows, and Explicit Likelihood Models, July 2021

مصطلحات موضوعية: Diffusion models, Generative models, Variational auto-encoders, Normalizing flows, DDPM, VAE, Engineering, computing & technology, Computer science, Ingénierie, informatique & technologie, Sciences informatiques

وصف الملف: 6

URL الوصول: https://orbi.uliege.be/handle/2268/262334

المؤلفون: Wehenkel, Antoine, Louppe, Gilles

المصدر: Proceedings of AISTATS 2021 (2021-04-13); The 24th International Conference on Artificial Intelligence and Statistics, April 2021

مصطلحات موضوعية: Normalizing Flows, Bayesian Networks, Density Estimation, Density Estimator, Probability Distribution, Machine Learning, Unsupervised Learning, Physical, chemical, mathematical & earth Sciences, Mathematics, Physique, chimie, mathématiques & sciences de la terre, Mathématiques

URL الوصول: https://orbi.uliege.be/handle/2268/252739

المؤلفون: Marc, Brice, Foucher, Philippe, Forbes, Florence, Charbonnier, Pierre

المساهمون: Evaluation non destructive des structures et des matériaux (ENDSUM), Centre d'Etudes et d'Expertise sur les Risques, l'Environnement, la Mobilité et l'Aménagement (Cerema), Modèles statistiques bayésiens et des valeurs extrêmes pour données structurées et de grande dimension (STATIFY), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Jean Kuntzmann (LJK), Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP), Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP), Université Grenoble Alpes (UGA)

المصدر: EUSIPCO 2024 - 32nd European conference on signal processing ; https://hal.science/hal-04715892 ; EUSIPCO 2024 - 32nd European conference on signal processing, Aug 2024, Lyon, France. pp.1-5

مصطلحات موضوعية: Anomaly detection, unsupervised learning, normalizing flows, [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]

جغرافية الموضوع: Lyon, France

الاتاحة: https://hal.science/hal-04715892
https://hal.science/hal-04715892v1/document
https://hal.science/hal-04715892v1/file/EUSIPCO%20%281%29.pdf

المؤلفون: Bekri, Naoufal El, Drumetz, Lucas, Vermet, Franck

المساهمون: Laboratoire de Mathématiques de Bretagne Atlantique (LMBA), Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS), Département Mathematical and Electrical Engineering (IMT Atlantique - MEE), IMT Atlantique (IMT Atlantique), Institut Mines-Télécom Paris (IMT)-Institut Mines-Télécom Paris (IMT), Equipe Observations Signal & Environnement (Lab-STICC_OSE), Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (Lab-STICC), École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom Paris (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom Paris (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom Paris (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom Paris (IMT), Océan Dynamique Observations Analyse (ODYSSEY), Université de Rennes (UR)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Université de Brest (UBO)-Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-IMT Atlantique (IMT Atlantique), ANR-21-CE48-0005,LEMONADE,Apprentissage et modélisation de la dynamique spectrale de séries temporelles d'images satellitaires(2021), ANR-11-LABX-0020,LEBESGUE,Centre de Mathématiques Henri Lebesgue : fondements, interactions, applications et Formation(2011)

المصدر: ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) ; https://imt-atlantique.hal.science/hal-04716987 ; ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Apr 2024, Seoul, France. pp.6395-6399, ⟨10.1109/ICASSP48485.2024.10446131⟩

مصطلحات موضوعية: Stochastic differential equations, deep generative models, normalizing flows, time series, convex neural network, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], [MATH.MATH-PR]Mathematics [math]/Probability [math.PR]

جغرافية الموضوع: Seoul, France

الاتاحة: https://imt-atlantique.hal.science/hal-04716987
https://imt-atlantique.hal.science/hal-04716987v1/document
https://imt-atlantique.hal.science/hal-04716987v1/file/Time_Change_Normalizing_Flow_v2.pdf
https://doi.org/10.1109/ICASSP48485.2024.10446131

المؤلفون: Souveton, Vincent, Guillin, Arnaud, Jasche, Jens, Lavaux, Guilhem, Michel, Manon

المساهمون: Laboratoire de Mathématiques Blaise Pascal (LMBP), Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA), Institut universitaire de France (IUF), Ministère de l'Education nationale, de l’Enseignement supérieur et de la Recherche (M.E.N.E.S.R.), Oskar Klein Centre Stockholm, Stockholm University, Institut d'Astrophysique de Paris (IAP), Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Université Clermont Auvergne 2017-2020 (UCA 2017-2020 )-Centre National de la Recherche Scientifique (CNRS), MITI-Prime 80 project ”CosmoBayes”, All the authors thank the Mésocentre Clermont Auvergne University (https://mesocentre.uca.fr/) and the HPC cluster at Fysikum (it.fysik.su.se/hpc/) for providing computing and storage resources., This work was supported by the Simons Collaboration on “Learning the Universe”., JJ acknowledges support by the Swedish Research Council (VR) under the project 2020-05143 – “Deciphering the Dynamics of Cosmic Structure”., ANR-20-CE46-0007,SuSa,Développer des algorithmes stochastiques scalables par non-réversibilité, parallélisation et schémas adaptifs(2020)

المصدر: Proceedings of the 27th International Conference on Artificial Intelligence and Statistics (AISTATS) 2024 ; 27th International Conference on Artificial Intelligence and Statistics (AISTATS) 2024 ; https://hal.science/hal-03976501 ; 27th International Conference on Artificial Intelligence and Statistics (AISTATS) 2024, May 2024, Valencia, France. ⟨10.48550/arXiv.2302.01955⟩

مصطلحات موضوعية: Generative models, Normalizing flows, Hamiltonian flows, Sampling, [INFO]Computer Science [cs]

جغرافية الموضوع: Valencia, France

Relation: info:eu-repo/semantics/altIdentifier/arxiv/2302.01955; ARXIV: 2302.01955

الاتاحة: https://hal.science/hal-03976501
https://hal.science/hal-03976501v1/document
https://hal.science/hal-03976501v1/file/NHF_paper_HAL.pdf
https://doi.org/10.48550/arXiv.2302.01955

المؤلفون: Ziyi Yin, Rafael Orozco, Mathias Louboutin, Felix J. Herrmann

المصدر: Advanced Modeling and Simulation in Engineering Sciences, Vol 10, Iss 1, Pp 1-27 (2023)

مصطلحات موضوعية: Fourier neural operators, Normalizing flows, Multiphysics, Deep learning, Learned surrogates, Learned constraints, Mechanics of engineering. Applied mechanics, TA349-359, Systems engineering, TA168

وصف الملف: electronic resource

Relation: https://doaj.org/toc/2213-7467

URL الوصول: https://doaj.org/article/2bcf55e60298452bb46b71fc20c9773d

المؤلفون: Wehenkel, Antoine, Louppe, Gilles

المصدر: ICML2020 Workshop on Invertible Neural Networks, Normalizing Flows, and Explicit Likelihood Models, July 2020

مصطلحات موضوعية: Normalizing Flows, Bayesian Networks, Density Estimation, Engineering, computing & technology, Computer science, Ingénierie, informatique & technologie, Sciences informatiques

وصف الملف: Antoine Wehenkel

URL الوصول: https://orbi.uliege.be/handle/2268/249062

المؤلفون: Patryk Wielopolski, Oleksii Furman, Maciej Zięba

المصدر: Entropy, Vol 26, Iss 7, p 593 (2024)

مصطلحات موضوعية: probabilistic regression, tabular data, normalizing flows, decision tree ensembles, neural decision tree, Science, Astrophysics, QB460-466, Physics, QC1-999

وصف الملف: electronic resource

Relation: https://www.mdpi.com/1099-4300/26/7/593; https://doaj.org/toc/1099-4300

URL الوصول: https://doaj.org/article/3d7724cabe1f45f3ba2039c5e0c13468

المؤلفون: Daniel Andrade

المصدر: Machine Learning: Science and Technology, Vol 5, Iss 4, p 045066 (2024)

مصطلحات موضوعية: normalizing flows, variational inference, marginal likelihood, horseshoe prior, Bayesian Lasso, logistic regression, Computer engineering. Computer hardware, TK7885-7895, Electronic computers. Computer science, QA75.5-76.95

Relation: https://doi.org/10.1088/2632-2153/ad9a39; https://doaj.org/toc/2632-2153; https://doaj.org/article/c1b8fbdcd66c433387d43adb4fd17a89

الاتاحة: https://doi.org/10.1088/2632-2153/ad9a39
https://doaj.org/article/c1b8fbdcd66c433387d43adb4fd17a89

المؤلفون: Coeurdoux, Florentin, Dobigeon, Nicolas, Chainais, Pierre

المساهمون: Signal et Communications (IRIT-SC), Institut de recherche en informatique de Toulouse (IRIT), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Toulouse Mind & Brain Institut (TMBI), Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT), Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), ANR-16-IDEX-0004,ULNE,ULNE(2016), ANR-19-P3IA-0004,ANITI,Artificial and Natural Intelligence Toulouse Institute(2019)

المصدر: ISSN: 0885-6125.

مصطلحات موضوعية: Normalizing flows, Generative models, Monte Carlo sampling, Metropolis adjusted Langevin algorithm, [STAT.ML]Statistics [stat]/Machine Learning [stat.ML]

Relation: info:eu-repo/semantics/altIdentifier/arxiv/2305.12149; ARXIV: 2305.12149

الاتاحة: https://hal.science/hal-04710673
https://hal.science/hal-04710673v1/document
https://hal.science/hal-04710673v1/file/Coeurdoux_ML_2024.pdf
https://doi.org/10.1007/s10994-024-06623-x

المؤلفون: Bo Liang, Minghui Du, He Wang, Yuxiang Xu, Chang Liu, Xiaotong Wei, Peng Xu, Li-e Qiang, Ziren Luo

المصدر: Machine Learning: Science and Technology, Vol 5, Iss 4, p 045040 (2024)

مصطلحات موضوعية: gravitational wave, massive black hole binaries, continuous normalizing flows, flow matching, Computer engineering. Computer hardware, TK7885-7895, Electronic computers. Computer science, QA75.5-76.95

Relation: https://doi.org/10.1088/2632-2153/ad8da9; https://doaj.org/toc/2632-2153; https://doaj.org/article/deff55d350cd436786009dc46ea69182

الاتاحة: https://doi.org/10.1088/2632-2153/ad8da9
https://doaj.org/article/deff55d350cd436786009dc46ea69182

المؤلفون: Białas, Piotr, Korcyl, Piotr, Stebel, Tomasz

مصطلحات موضوعية: Monte-carlo, normalizing flows, lattice field theory, machine learning

Relation: Computer Physics Communications, T. 298; https://ruj.uj.edu.pl/xmlui/handle/item/327368

الاتاحة: https://ruj.uj.edu.pl/xmlui/handle/item/327368
https://doi.org/10.1016/j.cpc.2024.109094

المؤلفون: Nishant Kumar, Lukas Krause, Thomas Wondrak, Sven Eckert, Kerstin Eckert, Stefan Gumhold

المصدر: Sensors, Vol 24, Iss 4, p 1213 (2024)

مصطلحات موضوعية: machine learning, invertible neural networks, normalizing flows, water electrolysis, Biot–Savart law, inverse problems, Chemical technology, TP1-1185

Relation: https://www.mdpi.com/1424-8220/24/4/1213; https://doaj.org/toc/1424-8220; https://doaj.org/article/3c73b3ef946d4876952a75d344ba919f

الاتاحة: https://doi.org/10.3390/s24041213
https://doaj.org/article/3c73b3ef946d4876952a75d344ba919f

المؤلفون: Matej Grcić, Petra Bevandić, Zoran Kalafatić, Siniša Šegvić

المصدر: Sensors, Vol 24, Iss 4, p 1248 (2024)

مصطلحات موضوعية: dense out-of-distribution detection, normalizing flows, semantic segmentation, autonomous driving, remote sensing, Chemical technology, TP1-1185

Relation: https://www.mdpi.com/1424-8220/24/4/1248; https://doaj.org/toc/1424-8220; https://doaj.org/article/1e0f819a0d6d46c58b7b716cc7615056

الاتاحة: https://doi.org/10.3390/s24041248
https://doaj.org/article/1e0f819a0d6d46c58b7b716cc7615056

المؤلفون: F Vaselli, F Cattafesta, P Asenov, A Rizzi

المصدر: Machine Learning: Science and Technology, Vol 5, Iss 3, p 035007 (2024)

مصطلحات موضوعية: normalizing flows, flow matching, machine learning, simulation, high energy physics, Computer engineering. Computer hardware, TK7885-7895, Electronic computers. Computer science, QA75.5-76.95

Relation: https://doi.org/10.1088/2632-2153/ad563c; https://doaj.org/toc/2632-2153; https://doaj.org/article/692eac720ab24c9fafe32cd06d999200

الاتاحة: https://doi.org/10.1088/2632-2153/ad563c
https://doaj.org/article/692eac720ab24c9fafe32cd06d999200