المؤلفون: Mujahid, Omer

المساهمون: University/Department: Universitat de Girona. Departament d'Enginyeria Elèctrica, Electrònica i Automàtica

مرشدي الرسالة: Vehí, Josep, Contreras, Ivan, Institut d'Informàtica i Aplicacions

المصدر: TDX (Tesis Doctorals en Xarxa)

مصطلحات موضوعية: Diabetis tipus 1, Type 1 diabetes, Diabetes tipo 1, Pacients virtuals, Virtual patients, Pacientes virtuales, Simuladors de Diabetis tipus 1, Type 1 diabetes simulators, Simuladores de diabetes tipo 1, síntesi causal de dades de glucosa a la sang, Causal blood glucose data synthesis, Síntesis causal de glucosa en la sangre, Síntesi condicional de dades de glucosa a la sang, Conditional blood glucose data synthesis, Síntesis condicional de dades de glucosa en la sangre, Models generatius profunds, Deep generative models, Modelos generativos profundos, Models basats en dades, Data-driven models, Modelos basados en datos

الوقت: 616.4, 621.3

وصف الملف: application/pdf

الوصول الحر: http://hdl.handle.net/10803/689606Test

المؤلفون: Cabrera Tejera, Alvis

المساهمون: University/Department: Universitat de Girona. Departament d'Enginyeria Elèctrica, Electrònica i Automàtica

مرشدي الرسالة: Vehí, Josep, Beneyto Tantiña, Aleix

المصدر: TDX (Tesis Doctorals en Xarxa)

مصطلحات موضوعية: Diabetis tipus 1, Diabetes tipo 1, Type 1 diabetes, Pacients virtuals, Pacientes virtuales, Virtual patients, Simuladors, Simuladores, Simulators, Glucosa a la sang, Glucosa en la sangre, Blood glucose, Dades composicionals, Datos composicionales, Compositional data, Models generatius profunds, Modelos generativos profundos, Deep generative models, Models basats en dades, Modelos basados en datos, Data-driven models, Diabetis mellitus

الوقت: 616.4, 621.3

وصف الملف: application/pdf

الوصول الحر: http://hdl.handle.net/10803/689607Test

المؤلفون: Ramires, António

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

مرشدي الرسالة: Serra, Xavier, Font Corbera, Frederic

المصدر: TDX (Tesis Doctorals en Xarxa)

مصطلحات موضوعية: Electronic music production, Instrument classification, Percussive sound generation, Music information retrieval, Deep learning, Deep generative models, Producción de música electrónica, Clasificación de instrumentos, Generación de sonidos percusivos, Recuperación de la información musical, Aprendizaje profundo, Modelos generativos profundos

وصف الملف: application/pdf

الوصول الحر: http://hdl.handle.net/10803/687697Test

المؤلفون: Deveshwar, Nikhil, Rajagopal, Abhejit, Sahin, Sule, Shimron, Efrat, Larson, Peder EZ

المصدر: Bioengineering. 10(3)

مصطلحات موضوعية: Engineering, Biomedical Engineering, Bioengineering, Biomedical Imaging, 4.1 Discovery and preclinical testing of markers and technologies, Detection, screening and diagnosis, synthetic phase, synthetic multi-coil data, deep generative models, GANs, generative adversarial network, synthetic data, MRI reconstruction, deep learning, unrolled networks, Biomedical engineering

وصف الملف: application/pdf

الوصول الحر: https://escholarship.org/uc/item/5p96987gTest

المؤلفون: Jingbin Xu, Degang Xu, Kun Wan, Ying Zhang

المصدر: Water Science and Technology, Vol 88, Iss 11, Pp 2762-2778 (2023)

مصطلحات موضوعية: data compensation, deep generative models, imbalanced samples, vae–wgan–gp model, water quality assessment, Environmental technology. Sanitary engineering, TD1-1066

وصف الملف: electronic resource

العلاقة: http://wst.iwaponline.com/content/88/11/2762Test; https://doaj.org/toc/0273-1223Test; https://doaj.org/toc/1996-9732Test

الوصول الحر: https://doaj.org/article/fa1d852eff50414cb1f3f808528cede3Test

المؤلفون: Iñigo Prada-Luengo, Viktoria Schuster, Yuhu Liang, Thilde Terkelsen, Valentina Sora, Anders Krogh

المصدر: Genome Biology, Vol 24, Iss 1, Pp 1-17 (2023)

مصطلحات موضوعية: Deep generative models, Deep learning, Differential expression analysis, DEG, DEseq2, Transcriptomics, Biology (General), QH301-705.5, Genetics, QH426-470

وصف الملف: electronic resource

العلاقة: https://doaj.org/toc/1474-760XTest

الوصول الحر: https://doaj.org/article/a01c7581a83340df990a066ff0394ff0Test

المؤلفون: Amit Gangwal, Azim Ansari, Iqrar Ahmad, Abul Kalam Azad, Vinoth Kumarasamy, Vetriselvan Subramaniyan, Ling Shing Wong

المصدر: Frontiers in Pharmacology, Vol 15 (2024)

مصطلحات موضوعية: ChatGPT, de novo drug design, deep generative models, AlphaFold, variational autoencoders, generative adversarial network, Therapeutics. Pharmacology, RM1-950

وصف الملف: electronic resource

العلاقة: https://www.frontiersin.org/articles/10.3389/fphar.2024.1331062/fullTest; https://doaj.org/toc/1663-9812Test

الوصول الحر: https://doaj.org/article/8074ab061f8049b08d0b9de47707813dTest

المؤلفون: van Krieken, Emile

المصدر: van Krieken , E 2024 , ' Optimisation in Neurosymbolic Learning Systems ' , PhD , Vrije Universiteit Amsterdam . https://doi.org/10.5463/thesis.466Test

مصطلحات موضوعية: Neurosymbolische Kunstmatige Intelligentie, Machinaal Leren, Leren met Achtergrondkennis, Diepe Generatieve Modellen, Fuzzy Logica, Probabilistische Logica, Probabilistisch Programmeren, Optimalisatie, Schatters van Gradiënten, Neurale Netwerken, Neurosymbolic Artificial Intelligence, Machine Learning, Learning with Background Knowledge, Deep Generative Models, Fuzzy Logic, Probabilistic Logic, Probabilistic Programming, Optimization, Gradient Estimation, Neural Networks

وصف الملف: application/pdf

العلاقة: https://research.vu.nl/en/publications/270d7b7c-be6a-4b07-a8c9-22cca8dd5e96Test

الإتاحة: https://doi.org/10.5463/thesis.466Test
https://research.vu.nl/en/publications/270d7b7c-be6a-4b07-a8c9-22cca8dd5e96Test
https://hdl.handle.net/1871.1/270d7b7c-be6a-4b07-a8c9-22cca8dd5e96Test
https://research.vu.nl/ws/files/282134811/phd%20thesis%20final%20-%20655f23e0eb769.pdfTest
https://research.vu.nl/ws/files/282134813/170489%20van%20krieken%20r13%20omsdefdpr%20-%20655f242c28257.pdfTest
https://research.vu.nl/ws/files/282134815/inhoudsopgave%20-%20655f23e7e96b2.pdfTest
https://research.vu.nl/ws/files/282134817/main-3-4%20-%206527c18438876.pdfTest

المؤلفون: Solal, Maëlys, Hassanaly, Ravi, Burgos, Ninon

المساهمون: Algorithms, models and methods for images and signals of the human brain = Algorithmes, modèles et méthodes pour les images et les signaux du cerveau humain ICM Paris (ARAMIS), Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière AP-HP, Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière AP-HP, Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), ANR-19-P3IA-0001,PRAIRIE,PaRis Artificial Intelligence Research InstitutE(2019), ANR-10-IAHU-0006,IHU-A-ICM,Institut de Neurosciences Translationnelles de Paris(2010)

المصدر: SPIE Medical Imaging ; https://hal.science/hal-04291561Test ; SPIE Medical Imaging, Feb 2024, San Diego (California), United States

مصطلحات موضوعية: Unsupervised anomaly detection, Deep generative models, Alzheimer's disease, Abnormality maps, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], [SCCO.NEUR]Cognitive science/Neuroscience, [SDV.IB.MN]Life Sciences [q-bio]/Bioengineering/Nuclear medicine

جغرافية الموضوع: San Diego (California), United States

العلاقة: info:eu-repo/semantics/altIdentifier/arxiv/2311.12081; hal-04291561; https://hal.science/hal-04291561Test; https://hal.science/hal-04291561v2/documentTest; https://hal.science/hal-04291561v2/file/SOLAL_SPIE-2024_CN-STD.pdfTest; ARXIV: 2311.12081

الإتاحة: https://hal.science/hal-04291561Test
https://hal.science/hal-04291561v2/documentTest
https://hal.science/hal-04291561v2/file/SOLAL_SPIE-2024_CN-STD.pdfTest

المؤلفون: Bongsung Bae, Haelee Bae, Hojung Nam

المصدر: Journal of Cheminformatics, Vol 15, Iss 1, Pp 1-18 (2023)

مصطلحات موضوعية: De novo drug design, Deep generative models, Reinforcement learning, Bioactivity optimization, Information technology, T58.5-58.64, Chemistry, QD1-999

وصف الملف: electronic resource

العلاقة: https://doaj.org/toc/1758-2946Test

الوصول الحر: https://doaj.org/article/c1989da341904f67a40940d73b85e5bcTest