Artículos de revistas sobre el tema "Constrained Gaussian processes"
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Wang, Xiaojing y James O. Berger. "Estimating Shape Constrained Functions Using Gaussian Processes". SIAM/ASA Journal on Uncertainty Quantification 4, n.º 1 (enero de 2016): 1–25. http://dx.doi.org/10.1137/140955033.
Texto completoGraf, Siegfried y Harald Luschgy. "Entropy-constrained functional quantization of Gaussian processes". Proceedings of the American Mathematical Society 133, n.º 11 (2 de mayo de 2005): 3403–9. http://dx.doi.org/10.1090/s0002-9939-05-07888-3.
Texto completoNiu, Mu, Pokman Cheung, Lizhen Lin, Zhenwen Dai, Neil Lawrence y David Dunson. "Intrinsic Gaussian processes on complex constrained domains". Journal of the Royal Statistical Society: Series B (Statistical Methodology) 81, n.º 3 (19 de abril de 2019): 603–27. http://dx.doi.org/10.1111/rssb.12320.
Texto completoGirbés-Juan, Vicent, Joaquín Moll, Antonio Sala y Leopoldo Armesto. "Cautious Bayesian Optimization: A Line Tracker Case Study". Sensors 23, n.º 16 (18 de agosto de 2023): 7266. http://dx.doi.org/10.3390/s23167266.
Texto completoYang, Shihao, Samuel W. K. Wong y S. C. Kou. "Inference of dynamic systems from noisy and sparse data via manifold-constrained Gaussian processes". Proceedings of the National Academy of Sciences 118, n.º 15 (9 de abril de 2021): e2020397118. http://dx.doi.org/10.1073/pnas.2020397118.
Texto completoRattunde, Leonhard, Igor Laptev, Edgar D. Klenske y Hans-Christian Möhring. "Safe optimization for feedrate scheduling of power-constrained milling processes by using Gaussian processes". Procedia CIRP 99 (2021): 127–32. http://dx.doi.org/10.1016/j.procir.2021.03.020.
Texto completoSchweidtmann, Artur M., Dominik Bongartz, Daniel Grothe, Tim Kerkenhoff, Xiaopeng Lin, Jaromił Najman y Alexander Mitsos. "Deterministic global optimization with Gaussian processes embedded". Mathematical Programming Computation 13, n.º 3 (25 de junio de 2021): 553–81. http://dx.doi.org/10.1007/s12532-021-00204-y.
Texto completoLi, Ming, Xiafei Tang, Qichun Zhang y Yiqun Zou. "Non-Gaussian Pseudolinear Kalman Filtering-Based Target Motion Analysis with State Constraints". Applied Sciences 12, n.º 19 (4 de octubre de 2022): 9975. http://dx.doi.org/10.3390/app12199975.
Texto completoSalmon, John. "Generation of Correlated and Constrained Gaussian Stochastic Processes for N-Body Simulations". Astrophysical Journal 460 (marzo de 1996): 59. http://dx.doi.org/10.1086/176952.
Texto completoRocher, Antoine, Vanina Ruhlmann-Kleider, Etienne Burtin y Arnaud de Mattia. "Halo occupation distribution of Emission Line Galaxies: fitting method with Gaussian processes". Journal of Cosmology and Astroparticle Physics 2023, n.º 05 (1 de mayo de 2023): 033. http://dx.doi.org/10.1088/1475-7516/2023/05/033.
Texto completoLindberg, Christina Willecke, Daniela Huppenkothen, R. Lynne Jones, Bryce T. Bolin, Mario Jurić, V. Zach Golkhou, Eric C. Bellm et al. "Characterizing Sparse Asteroid Light Curves with Gaussian Processes". Astronomical Journal 163, n.º 1 (21 de diciembre de 2021): 29. http://dx.doi.org/10.3847/1538-3881/ac3079.
Texto completoWang, Shengbo y Ke Li. "Constrained Bayesian Optimization under Partial Observations: Balanced Improvements and Provable Convergence". Proceedings of the AAAI Conference on Artificial Intelligence 38, n.º 14 (24 de marzo de 2024): 15607–15. http://dx.doi.org/10.1609/aaai.v38i14.29488.
Texto completoSchrouff, Jessica, Caroline Kussé, Louis Wehenkel, Pierre Maquet y Christophe Phillips. "Decoding Semi-Constrained Brain Activity from fMRI Using Support Vector Machines and Gaussian Processes". PLoS ONE 7, n.º 4 (26 de abril de 2012): e35860. http://dx.doi.org/10.1371/journal.pone.0035860.
Texto completoLi, Wei, Philippe Ciais, Shushi Peng, Chao Yue, Yilong Wang, Martin Thurner, Sassan S. Saatchi et al. "Land-use and land-cover change carbon emissions between 1901 and 2012 constrained by biomass observations". Biogeosciences 14, n.º 22 (14 de noviembre de 2017): 5053–67. http://dx.doi.org/10.5194/bg-14-5053-2017.
Texto completoDuecker, Daniel Andre, Andreas Rene Geist, Edwin Kreuzer y Eugen Solowjow. "Learning Environmental Field Exploration with Computationally Constrained Underwater Robots: Gaussian Processes Meet Stochastic Optimal Control". Sensors 19, n.º 9 (6 de mayo de 2019): 2094. http://dx.doi.org/10.3390/s19092094.
Texto completoMinkova, Leda D. "A stochastic model for the financial market with discontinuous prices". Journal of Applied Mathematics and Stochastic Analysis 9, n.º 3 (1 de enero de 1996): 271–80. http://dx.doi.org/10.1155/s1048953396000263.
Texto completoLi, Lei, Zhen Gao, Yu-Tian Wang, Ming-Wen Zhang, Jian-Cheng Ni, Chun-Hou Zheng y Yansen Su. "SCMFMDA: Predicting microRNA-disease associations based on similarity constrained matrix factorization". PLOS Computational Biology 17, n.º 7 (12 de julio de 2021): e1009165. http://dx.doi.org/10.1371/journal.pcbi.1009165.
Texto completoDEKKER, H. y A. MAASSEN VAN DEN BRINK. "TRANSITION STATE THEORY IN EXTENDED PHASE SPACE". Modern Physics Letters B 07, n.º 19 (20 de agosto de 1993): 1263–68. http://dx.doi.org/10.1142/s0217984993001284.
Texto completoGuo, Wei, Tianhong Pan, Zhengming Li y Shan Chen. "Batch process modeling by using temporal feature and Gaussian mixture model". Transactions of the Institute of Measurement and Control 42, n.º 6 (1 de diciembre de 2019): 1204–14. http://dx.doi.org/10.1177/0142331219887827.
Texto completoLivieris, Ioannis E., Emmanuel Pintelas, Theodore Kotsilieris, Stavros Stavroyiannis y Panagiotis Pintelas. "Weight-Constrained Neural Networks in Forecasting Tourist Volumes: A Case Study". Electronics 8, n.º 9 (8 de septiembre de 2019): 1005. http://dx.doi.org/10.3390/electronics8091005.
Texto completoRegayre, Leighton A., Lucia Deaconu, Daniel P. Grosvenor, David M. H. Sexton, Christopher Symonds, Tom Langton, Duncan Watson-Paris et al. "Identifying climate model structural inconsistencies allows for tight constraint of aerosol radiative forcing". Atmospheric Chemistry and Physics 23, n.º 15 (8 de agosto de 2023): 8749–68. http://dx.doi.org/10.5194/acp-23-8749-2023.
Texto completoCandelieri, Antonio, Andrea Ponti, Elisabetta Fersini, Enza Messina y Francesco Archetti. "Safe Optimal Control of Dynamic Systems: Learning from Experts and Safely Exploring New Policies". Mathematics 11, n.º 20 (19 de octubre de 2023): 4347. http://dx.doi.org/10.3390/math11204347.
Texto completoLi, S.-S., W. Zang, A. Udalski, Y. Shvartzvald, D. Huber, C.-U. Lee, T. Sumi et al. "OGLE-2017-BLG-1186: first application of asteroseismology and Gaussian processes to microlensing". Monthly Notices of the Royal Astronomical Society 488, n.º 3 (10 de julio de 2019): 3308–23. http://dx.doi.org/10.1093/mnras/stz1873.
Texto completoWenk, Philippe, Gabriele Abbati, Michael A. Osborne, Bernhard Schölkopf, Andreas Krause y Stefan Bauer. "ODIN: ODE-Informed Regression for Parameter and State Inference in Time-Continuous Dynamical Systems". Proceedings of the AAAI Conference on Artificial Intelligence 34, n.º 04 (3 de abril de 2020): 6364–71. http://dx.doi.org/10.1609/aaai.v34i04.6106.
Texto completoNi, Jiancheng, Lei Li, Yutian Wang, Cunmei Ji y Chunhou Zheng. "MDSCMF: Matrix Decomposition and Similarity-Constrained Matrix Factorization for miRNA–Disease Association Prediction". Genes 13, n.º 6 (6 de junio de 2022): 1021. http://dx.doi.org/10.3390/genes13061021.
Texto completoNi, Jiancheng, Lei Li, Yutian Wang, Cunmei Ji y Chunhou Zheng. "MDSCMF: Matrix Decomposition and Similarity-Constrained Matrix Factorization for miRNA–Disease Association Prediction". Genes 13, n.º 6 (6 de junio de 2022): 1021. http://dx.doi.org/10.3390/genes13061021.
Texto completoHERZOG, FLORIAN, GABRIEL DONDI y HANS P. GEERING. "STOCHASTIC MODEL PREDICTIVE CONTROL AND PORTFOLIO OPTIMIZATION". International Journal of Theoretical and Applied Finance 10, n.º 02 (marzo de 2007): 203–33. http://dx.doi.org/10.1142/s0219024907004196.
Texto completoLi, Kaibin, Zhiping Peng, Delong Cui y Qirui Li. "SLA-DQTS: SLA Constrained Adaptive Online Task Scheduling Based on DDQN in Cloud Computing". Applied Sciences 11, n.º 20 (9 de octubre de 2021): 9360. http://dx.doi.org/10.3390/app11209360.
Texto completoMIELCZAREK, JAKUB y MICHAŁ KAMIONKA. "SMOOTHED QUANTUM FLUCTUATIONS AND CMB OBSERVATIONS". International Journal of Modern Physics D 21, n.º 10 (octubre de 2012): 1250080. http://dx.doi.org/10.1142/s0218271812500800.
Texto completoRamalingam, Gomathi, Selvakumaran Selvaraj, Visumathi James, Senthil Kumar Saravanaperumal y Buvaneswari Mohanram. "Segmentation of Medical Images with Adaptable Multifunctional Discretization Bayesian Neural Networks and Gaussian Operation". International journal of electrical and computer engineering systems 14, n.º 4 (26 de abril de 2023): 381–92. http://dx.doi.org/10.32985/ijeces.14.4.2.
Texto completoShojaie, Ali y Emily B. Fox. "Granger Causality: A Review and Recent Advances". Annual Review of Statistics and Its Application 9, n.º 1 (7 de marzo de 2022): 289–319. http://dx.doi.org/10.1146/annurev-statistics-040120-010930.
Texto completoFaria, J. P., V. Adibekyan, E. M. Amazo-Gómez, S. C. C. Barros, J. D. Camacho, O. Demangeon, P. Figueira et al. "Decoding the radial velocity variations of HD 41248 with ESPRESSO". Astronomy & Astrophysics 635 (marzo de 2020): A13. http://dx.doi.org/10.1051/0004-6361/201936389.
Texto completoStrocchi, Marina, Stefano Longobardi, Christoph M. Augustin, Matthias A. F. Gsell, Argyrios Petras, Christopher A. Rinaldi, Edward J. Vigmond et al. "Cell to whole organ global sensitivity analysis on a four-chamber heart electromechanics model using Gaussian processes emulators". PLOS Computational Biology 19, n.º 6 (26 de junio de 2023): e1011257. http://dx.doi.org/10.1371/journal.pcbi.1011257.
Texto completoOwen, Nathan E. y Lorena Liuzzo. "Impact of land use on water resources via a Gaussian process emulator with dimension reduction". Journal of Hydroinformatics 21, n.º 3 (19 de marzo de 2019): 411–26. http://dx.doi.org/10.2166/hydro.2019.067.
Texto completoMeyer, Antoine D., David A. van Dyk, Hyungsuk Tak y Aneta Siemiginowska. "TD-CARMA: Painless, Accurate, and Scalable Estimates of Gravitational Lens Time Delays with Flexible CARMA Processes". Astrophysical Journal 950, n.º 1 (1 de junio de 2023): 37. http://dx.doi.org/10.3847/1538-4357/acbea1.
Texto completoWang, Yufei, Renjie Wan, Wenhan Yang, Haoliang Li, Lap-Pui Chau y Alex Kot. "Low-Light Image Enhancement with Normalizing Flow". Proceedings of the AAAI Conference on Artificial Intelligence 36, n.º 3 (28 de junio de 2022): 2604–12. http://dx.doi.org/10.1609/aaai.v36i3.20162.
Texto completoCasaburo, Alessandro, Dario Magliacano, Giuseppe Petrone, Francesco Franco y Sergio De Rosa. "Gaussian-Based Machine Learning Algorithm for the Design and Characterization of a Porous Meta-Material for Acoustic Applications". Applied Sciences 12, n.º 1 (30 de diciembre de 2021): 333. http://dx.doi.org/10.3390/app12010333.
Texto completoVacher, Jonathan, Andrew Isaac Meso, Laurent U. Perrinet y Gabriel Peyré. "Bayesian Modeling of Motion Perception Using Dynamical Stochastic Textures". Neural Computation 30, n.º 12 (diciembre de 2018): 3355–92. http://dx.doi.org/10.1162/neco_a_01142.
Texto completoShang, Zhenhong, Ziqi He y Runxin Li. "A Coronal Loop Automatic Detection Method". Symmetry 16, n.º 6 (6 de junio de 2024): 704. http://dx.doi.org/10.3390/sym16060704.
Texto completoPollard, Oliver G., Natasha L. M. Barlow, Lauren J. Gregoire, Natalya Gomez, Víctor Cartelle, Jeremy C. Ely y Lachlan C. Astfalck. "Quantifying the uncertainty in the Eurasian ice-sheet geometry at the Penultimate Glacial Maximum (Marine Isotope Stage 6)". Cryosphere 17, n.º 11 (10 de noviembre de 2023): 4751–77. http://dx.doi.org/10.5194/tc-17-4751-2023.
Texto completoChang, W., P. J. Applegate, M. Haran y K. Keller. "Probabilistic calibration of a Greenland Ice Sheet model using spatially resolved synthetic observations: toward projections of ice mass loss with uncertainties". Geoscientific Model Development 7, n.º 5 (5 de septiembre de 2014): 1933–43. http://dx.doi.org/10.5194/gmd-7-1933-2014.
Texto completoChang, W., P. J. Applegate, M. Haran y K. Keller. "Probabilistic calibration of a Greenland Ice Sheet model using spatially-resolved synthetic observations: toward projections of ice mass loss with uncertainties". Geoscientific Model Development Discussions 7, n.º 2 (25 de marzo de 2014): 1905–31. http://dx.doi.org/10.5194/gmdd-7-1905-2014.
Texto completoSmit, Merijn, Andrej Dvornik, Mario Radovich, Konrad Kuijken, Matteo Maturi, Lauro Moscardini y Mauro Sereno. "AMICO galaxy clusters in KiDS-DR3: The impact of estimator statistics on the luminosity-mass scaling relation". Astronomy & Astrophysics 659 (marzo de 2022): A195. http://dx.doi.org/10.1051/0004-6361/202141626.
Texto completoDur, Tolga Hasan, Rossella Arcucci, Laetitia Mottet, Miguel Molina Solana, Christopher Pain y Yi-Ke Guo. "Weak Constraint Gaussian Processes for optimal sensor placement". Journal of Computational Science 42 (abril de 2020): 101110. http://dx.doi.org/10.1016/j.jocs.2020.101110.
Texto completoFurmanek, Mariusz P., Madhur Mangalam, Damian G. Kelty-Stephen y Grzegorz Juras. "Postural constraints recruit shorter-timescale processes into the non-Gaussian cascade processes". Neuroscience Letters 741 (enero de 2021): 135508. http://dx.doi.org/10.1016/j.neulet.2020.135508.
Texto completoBachoc, François, Agnès Lagnoux y Andrés F. López-Lopera. "Maximum likelihood estimation for Gaussian processes under inequality constraints". Electronic Journal of Statistics 13, n.º 2 (2019): 2921–69. http://dx.doi.org/10.1214/19-ejs1587.
Texto completoWilliams, M., A. D. Richardson, M. Reichstein, P. C. Stoy, P. Peylin, H. Verbeeck, N. Carvalhais et al. "Improving land surface models with FLUXNET data". Biogeosciences Discussions 6, n.º 2 (5 de marzo de 2009): 2785–835. http://dx.doi.org/10.5194/bgd-6-2785-2009.
Texto completoWilliams, M., A. D. Richardson, M. Reichstein, P. C. Stoy, P. Peylin, H. Verbeeck, N. Carvalhais et al. "Improving land surface models with FLUXNET data". Biogeosciences 6, n.º 7 (30 de julio de 2009): 1341–59. http://dx.doi.org/10.5194/bg-6-1341-2009.
Texto completoMcClintock, Thomas y Eduardo Rozo. "Reconstructing probability distributions with Gaussian processes". Monthly Notices of the Royal Astronomical Society 489, n.º 3 (2 de septiembre de 2019): 4155–60. http://dx.doi.org/10.1093/mnras/stz2426.
Texto completoRoque, Luis, Luis Torgo y Carlos Soares. "Automatic Hierarchical Time-Series Forecasting Using Gaussian Processes". Engineering Proceedings 5, n.º 1 (9 de julio de 2021): 49. http://dx.doi.org/10.3390/engproc2021005049.
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