Artigos de revistas sobre o tema "Constrained Gaussian processes"
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Wang, Xiaojing, e James O. Berger. "Estimating Shape Constrained Functions Using Gaussian Processes". SIAM/ASA Journal on Uncertainty Quantification 4, n.º 1 (janeiro de 2016): 1–25. http://dx.doi.org/10.1137/140955033.
Texto completo da fonteGraf, Siegfried, e Harald Luschgy. "Entropy-constrained functional quantization of Gaussian processes". Proceedings of the American Mathematical Society 133, n.º 11 (2 de maio de 2005): 3403–9. http://dx.doi.org/10.1090/s0002-9939-05-07888-3.
Texto completo da fonteNiu, Mu, Pokman Cheung, Lizhen Lin, Zhenwen Dai, Neil Lawrence e 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 completo da fonteGirbés-Juan, Vicent, Joaquín Moll, Antonio Sala e 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 completo da fonteYang, Shihao, Samuel W. K. Wong e 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 completo da fonteRattunde, Leonhard, Igor Laptev, Edgar D. Klenske e 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 completo da fonteSchweidtmann, Artur M., Dominik Bongartz, Daniel Grothe, Tim Kerkenhoff, Xiaopeng Lin, Jaromił Najman e Alexander Mitsos. "Deterministic global optimization with Gaussian processes embedded". Mathematical Programming Computation 13, n.º 3 (25 de junho de 2021): 553–81. http://dx.doi.org/10.1007/s12532-021-00204-y.
Texto completo da fonteLi, Ming, Xiafei Tang, Qichun Zhang e Yiqun Zou. "Non-Gaussian Pseudolinear Kalman Filtering-Based Target Motion Analysis with State Constraints". Applied Sciences 12, n.º 19 (4 de outubro de 2022): 9975. http://dx.doi.org/10.3390/app12199975.
Texto completo da fonteSalmon, John. "Generation of Correlated and Constrained Gaussian Stochastic Processes for N-Body Simulations". Astrophysical Journal 460 (março de 1996): 59. http://dx.doi.org/10.1086/176952.
Texto completo da fonteRocher, Antoine, Vanina Ruhlmann-Kleider, Etienne Burtin e 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 maio de 2023): 033. http://dx.doi.org/10.1088/1475-7516/2023/05/033.
Texto completo da fonteLindberg, 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 dezembro de 2021): 29. http://dx.doi.org/10.3847/1538-3881/ac3079.
Texto completo da fonteWang, Shengbo, e 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 março de 2024): 15607–15. http://dx.doi.org/10.1609/aaai.v38i14.29488.
Texto completo da fonteSchrouff, Jessica, Caroline Kussé, Louis Wehenkel, Pierre Maquet e 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 completo da fonteLi, 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 novembro de 2017): 5053–67. http://dx.doi.org/10.5194/bg-14-5053-2017.
Texto completo da fonteDuecker, Daniel Andre, Andreas Rene Geist, Edwin Kreuzer e Eugen Solowjow. "Learning Environmental Field Exploration with Computationally Constrained Underwater Robots: Gaussian Processes Meet Stochastic Optimal Control". Sensors 19, n.º 9 (6 de maio de 2019): 2094. http://dx.doi.org/10.3390/s19092094.
Texto completo da fonteMinkova, 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 janeiro de 1996): 271–80. http://dx.doi.org/10.1155/s1048953396000263.
Texto completo da fonteLi, Lei, Zhen Gao, Yu-Tian Wang, Ming-Wen Zhang, Jian-Cheng Ni, Chun-Hou Zheng e Yansen Su. "SCMFMDA: Predicting microRNA-disease associations based on similarity constrained matrix factorization". PLOS Computational Biology 17, n.º 7 (12 de julho de 2021): e1009165. http://dx.doi.org/10.1371/journal.pcbi.1009165.
Texto completo da fonteDEKKER, H., e 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 completo da fonteGuo, Wei, Tianhong Pan, Zhengming Li e 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 dezembro de 2019): 1204–14. http://dx.doi.org/10.1177/0142331219887827.
Texto completo da fonteLivieris, Ioannis E., Emmanuel Pintelas, Theodore Kotsilieris, Stavros Stavroyiannis e Panagiotis Pintelas. "Weight-Constrained Neural Networks in Forecasting Tourist Volumes: A Case Study". Electronics 8, n.º 9 (8 de setembro de 2019): 1005. http://dx.doi.org/10.3390/electronics8091005.
Texto completo da fonteRegayre, 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 completo da fonteCandelieri, Antonio, Andrea Ponti, Elisabetta Fersini, Enza Messina e Francesco Archetti. "Safe Optimal Control of Dynamic Systems: Learning from Experts and Safely Exploring New Policies". Mathematics 11, n.º 20 (19 de outubro de 2023): 4347. http://dx.doi.org/10.3390/math11204347.
Texto completo da fonteLi, 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 julho de 2019): 3308–23. http://dx.doi.org/10.1093/mnras/stz1873.
Texto completo da fonteWenk, Philippe, Gabriele Abbati, Michael A. Osborne, Bernhard Schölkopf, Andreas Krause e 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 completo da fonteNi, Jiancheng, Lei Li, Yutian Wang, Cunmei Ji e Chunhou Zheng. "MDSCMF: Matrix Decomposition and Similarity-Constrained Matrix Factorization for miRNA–Disease Association Prediction". Genes 13, n.º 6 (6 de junho de 2022): 1021. http://dx.doi.org/10.3390/genes13061021.
Texto completo da fonteNi, Jiancheng, Lei Li, Yutian Wang, Cunmei Ji e Chunhou Zheng. "MDSCMF: Matrix Decomposition and Similarity-Constrained Matrix Factorization for miRNA–Disease Association Prediction". Genes 13, n.º 6 (6 de junho de 2022): 1021. http://dx.doi.org/10.3390/genes13061021.
Texto completo da fonteHERZOG, FLORIAN, GABRIEL DONDI e HANS P. GEERING. "STOCHASTIC MODEL PREDICTIVE CONTROL AND PORTFOLIO OPTIMIZATION". International Journal of Theoretical and Applied Finance 10, n.º 02 (março de 2007): 203–33. http://dx.doi.org/10.1142/s0219024907004196.
Texto completo da fonteLi, Kaibin, Zhiping Peng, Delong Cui e Qirui Li. "SLA-DQTS: SLA Constrained Adaptive Online Task Scheduling Based on DDQN in Cloud Computing". Applied Sciences 11, n.º 20 (9 de outubro de 2021): 9360. http://dx.doi.org/10.3390/app11209360.
Texto completo da fonteMIELCZAREK, JAKUB, e MICHAŁ KAMIONKA. "SMOOTHED QUANTUM FLUCTUATIONS AND CMB OBSERVATIONS". International Journal of Modern Physics D 21, n.º 10 (outubro de 2012): 1250080. http://dx.doi.org/10.1142/s0218271812500800.
Texto completo da fonteRamalingam, Gomathi, Selvakumaran Selvaraj, Visumathi James, Senthil Kumar Saravanaperumal e 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 completo da fonteShojaie, Ali, e Emily B. Fox. "Granger Causality: A Review and Recent Advances". Annual Review of Statistics and Its Application 9, n.º 1 (7 de março de 2022): 289–319. http://dx.doi.org/10.1146/annurev-statistics-040120-010930.
Texto completo da fonteFaria, 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 (março de 2020): A13. http://dx.doi.org/10.1051/0004-6361/201936389.
Texto completo da fonteStrocchi, 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 junho de 2023): e1011257. http://dx.doi.org/10.1371/journal.pcbi.1011257.
Texto completo da fonteOwen, Nathan E., e 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 março de 2019): 411–26. http://dx.doi.org/10.2166/hydro.2019.067.
Texto completo da fonteMeyer, Antoine D., David A. van Dyk, Hyungsuk Tak e 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 junho de 2023): 37. http://dx.doi.org/10.3847/1538-4357/acbea1.
Texto completo da fonteWang, Yufei, Renjie Wan, Wenhan Yang, Haoliang Li, Lap-Pui Chau e Alex Kot. "Low-Light Image Enhancement with Normalizing Flow". Proceedings of the AAAI Conference on Artificial Intelligence 36, n.º 3 (28 de junho de 2022): 2604–12. http://dx.doi.org/10.1609/aaai.v36i3.20162.
Texto completo da fonteCasaburo, Alessandro, Dario Magliacano, Giuseppe Petrone, Francesco Franco e 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 dezembro de 2021): 333. http://dx.doi.org/10.3390/app12010333.
Texto completo da fonteVacher, Jonathan, Andrew Isaac Meso, Laurent U. Perrinet e Gabriel Peyré. "Bayesian Modeling of Motion Perception Using Dynamical Stochastic Textures". Neural Computation 30, n.º 12 (dezembro de 2018): 3355–92. http://dx.doi.org/10.1162/neco_a_01142.
Texto completo da fonteShang, Zhenhong, Ziqi He e Runxin Li. "A Coronal Loop Automatic Detection Method". Symmetry 16, n.º 6 (6 de junho de 2024): 704. http://dx.doi.org/10.3390/sym16060704.
Texto completo da fontePollard, Oliver G., Natasha L. M. Barlow, Lauren J. Gregoire, Natalya Gomez, Víctor Cartelle, Jeremy C. Ely e 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 novembro de 2023): 4751–77. http://dx.doi.org/10.5194/tc-17-4751-2023.
Texto completo da fonteChang, W., P. J. Applegate, M. Haran e 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 setembro de 2014): 1933–43. http://dx.doi.org/10.5194/gmd-7-1933-2014.
Texto completo da fonteChang, W., P. J. Applegate, M. Haran e 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 março de 2014): 1905–31. http://dx.doi.org/10.5194/gmdd-7-1905-2014.
Texto completo da fonteSmit, Merijn, Andrej Dvornik, Mario Radovich, Konrad Kuijken, Matteo Maturi, Lauro Moscardini e Mauro Sereno. "AMICO galaxy clusters in KiDS-DR3: The impact of estimator statistics on the luminosity-mass scaling relation". Astronomy & Astrophysics 659 (março de 2022): A195. http://dx.doi.org/10.1051/0004-6361/202141626.
Texto completo da fonteDur, Tolga Hasan, Rossella Arcucci, Laetitia Mottet, Miguel Molina Solana, Christopher Pain e 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 completo da fonteFurmanek, Mariusz P., Madhur Mangalam, Damian G. Kelty-Stephen e Grzegorz Juras. "Postural constraints recruit shorter-timescale processes into the non-Gaussian cascade processes". Neuroscience Letters 741 (janeiro de 2021): 135508. http://dx.doi.org/10.1016/j.neulet.2020.135508.
Texto completo da fonteBachoc, François, Agnès Lagnoux e 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 completo da fonteWilliams, 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 março de 2009): 2785–835. http://dx.doi.org/10.5194/bgd-6-2785-2009.
Texto completo da fonteWilliams, 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 julho de 2009): 1341–59. http://dx.doi.org/10.5194/bg-6-1341-2009.
Texto completo da fonteMcClintock, Thomas, e Eduardo Rozo. "Reconstructing probability distributions with Gaussian processes". Monthly Notices of the Royal Astronomical Society 489, n.º 3 (2 de setembro de 2019): 4155–60. http://dx.doi.org/10.1093/mnras/stz2426.
Texto completo da fonteRoque, Luis, Luis Torgo e Carlos Soares. "Automatic Hierarchical Time-Series Forecasting Using Gaussian Processes". Engineering Proceedings 5, n.º 1 (9 de julho de 2021): 49. http://dx.doi.org/10.3390/engproc2021005049.
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