Libros sobre el tema "Deep learning with uncertainty"
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Marchau, Vincent A. W. J., Warren E. Walker, Pieter J. T. M. Bloemen y Steven W. Popper, eds. Decision Making under Deep Uncertainty. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-05252-2.
Texto completoSaefken, Benjamin, Alexander Silbersdorff y Christoph Weisser, eds. Learning deep. Göttingen: Göttingen University Press, 2020. http://dx.doi.org/10.17875/gup2020-1338.
Texto completoBishop, Christopher M. y Hugh Bishop. Deep Learning. Cham: Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-45468-4.
Texto completoKruse, René-Marcel, Benjamin Säfken, Alexander Silbersdorff y Christoph Weisser, eds. Learning Deep Textwork. Göttingen: Göttingen University Press, 2021. http://dx.doi.org/10.17875/gup2021-1608.
Texto completoRodriguez, Andres. Deep Learning Systems. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-031-01769-8.
Texto completoFergus, Paul y Carl Chalmers. Applied Deep Learning. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-04420-5.
Texto completoCalin, Ovidiu. Deep Learning Architectures. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-36721-3.
Texto completoEl-Amir, Hisham y Mahmoud Hamdy. Deep Learning Pipeline. Berkeley, CA: Apress, 2020. http://dx.doi.org/10.1007/978-1-4842-5349-6.
Texto completoMatsushita, Kayo, ed. Deep Active Learning. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-5660-4.
Texto completoMichelucci, Umberto. Applied Deep Learning. Berkeley, CA: Apress, 2018. http://dx.doi.org/10.1007/978-1-4842-3790-8.
Texto completoMoons, Bert, Daniel Bankman y Marian Verhelst. Embedded Deep Learning. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-99223-5.
Texto completoWani, M. Arif, Mehmed Kantardzic y Moamar Sayed-Mouchaweh, eds. Deep Learning Applications. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-1816-4.
Texto completoDong, Hao, Zihan Ding y Shanghang Zhang, eds. Deep Reinforcement Learning. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-4095-0.
Texto completoKim, Phil. MATLAB Deep Learning. Berkeley, CA: Apress, 2017. http://dx.doi.org/10.1007/978-1-4842-2845-6.
Texto completoSewak, Mohit. Deep Reinforcement Learning. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-8285-7.
Texto completoGamba, Jonah. Deep Learning Models. Singapore: Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-99-9672-8.
Texto completoJo, Taeho. Deep Learning Foundations. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-32879-4.
Texto completoSingaram, Jayakumar, S. S. Iyengar y Azad M. Madni. Deep Learning Networks. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-39244-3.
Texto completoEnrique, Castillo. Expert systems: Uncertainty and learning. Southampton: Computational Mechanics, 1991.
Buscar texto completoHu, Fei y Xiali Hei. AI, Machine Learning and Deep Learning. Boca Raton: CRC Press, 2023. http://dx.doi.org/10.1201/9781003187158.
Texto completoKetkar, Nikhil y Jojo Moolayil. Deep Learning with Python. Berkeley, CA: Apress, 2021. http://dx.doi.org/10.1007/978-1-4842-5364-9.
Texto completoKim, Kwangjo y Harry Chandra Tanuwidjaja. Privacy-Preserving Deep Learning. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-3764-3.
Texto completoBenois-Pineau, Jenny y Akka Zemmari, eds. Multi-faceted Deep Learning. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-74478-6.
Texto completoYe, Jong Chul. Geometry of Deep Learning. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-6046-7.
Texto completoAhmed, Khaled R. y Henry Hexmoor, eds. Blockchain and Deep Learning. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-95419-2.
Texto completoBetti, Alessandro, Marco Gori y Stefano Melacci. Deep Learning to See. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-90987-1.
Texto completoBetti, Alessandro, Marco Gori y Stefano Melacci. Deep Learning to See. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-90987-1.
Texto completoPaluszek, Michael, Stephanie Thomas y Eric Ham. Practical MATLAB Deep Learning. Berkeley, CA: Apress, 2022. http://dx.doi.org/10.1007/978-1-4842-7912-0.
Texto completoWani, M. Arif, Farooq Ahmad Bhat, Saduf Afzal y Asif Iqbal Khan. Advances in Deep Learning. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-13-6794-6.
Texto completoMichelucci, Umberto. Advanced Applied Deep Learning. Berkeley, CA: Apress, 2019. http://dx.doi.org/10.1007/978-1-4842-4976-5.
Texto completoPaluszek, Michael y Stephanie Thomas. Practical MATLAB Deep Learning. Berkeley, CA: Apress, 2020. http://dx.doi.org/10.1007/978-1-4842-5124-9.
Texto completoSalvaris, Mathew, Danielle Dean y Wee Hyong Tok. Deep Learning with Azure. Berkeley, CA: Apress, 2018. http://dx.doi.org/10.1007/978-1-4842-3679-6.
Texto completoBhanu, Bir y Ajay Kumar, eds. Deep Learning for Biometrics. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-61657-5.
Texto completoGhatak, Abhijit. Deep Learning with R. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-5850-0.
Texto completoSkansi, Sandro. Introduction to Deep Learning. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-73004-2.
Texto completoKetkar, Nikhil. Deep Learning with Python. Berkeley, CA: Apress, 2017. http://dx.doi.org/10.1007/978-1-4842-2766-4.
Texto completoAmaratunga, Thimira. Deep Learning on Windows. Berkeley, CA: Apress, 2021. http://dx.doi.org/10.1007/978-1-4842-6431-7.
Texto completoChen, Yen-Wei y Lakhmi C. Jain, eds. Deep Learning in Healthcare. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-32606-7.
Texto completoTanaka, Akinori, Akio Tomiya y Koji Hashimoto. Deep Learning and Physics. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-6108-9.
Texto completoBruno, Michael A. Error and Uncertainty in Diagnostic Radiology. Oxford University Press, 2019. http://dx.doi.org/10.1093/med/9780190665395.001.0001.
Texto completoTutino, Stefania. Uncertainty in Post-Reformation Catholicism. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780190694098.001.0001.
Texto completoWalker, Warren E., Steven W. Popper y Pieter J T M Bloemen. Decision Making Under Deep Uncertainty. Saint Philip Street Press, 2020.
Buscar texto completoWalker, Warren E., Steven W. Popper y Pieter J T M Bloemen. Decision Making Under Deep Uncertainty. Saint Philip Street Press, 2020.
Buscar texto completoWang, Xizhao y Junhai Zhai. Learning with Uncertainty. Taylor & Francis Group, 2016.
Buscar texto completoWang, Xizhao y Junhai Zhai. Learning with Uncertainty. Taylor & Francis Group, 2016.
Buscar texto completoWang, Xizhao y Junhai Zhai. Learning with Uncertainty. Taylor & Francis Group, 2020.
Buscar texto completoWang, Xizhao y Junhai Zhai. Learning with Uncertainty. Taylor & Francis Group, 2016.
Buscar texto completoWang, Xizhao y Junhai Zhai. Learning with Uncertainty. Taylor & Francis Group, 2016.
Buscar texto completoWang, Xizhao y Junhai Zhai. Learning with Uncertainty. Taylor & Francis Group, 2016.
Buscar texto completoKelleher, John D. Deep Learning. MIT Press, 2019.
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