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1. Path integrals for stochastic processes
: an introduction
by Wio, Horacio S
2013, ISBN 9789814447997, xiii, 159
Stochastic integrals | Function spaces
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2. Stable non-Gaussian random processes: Stochastic models with infinite variance
by Samoradnitsky, Gennady and Taqqu, Murad S
01/2017, ISBN 0412051710
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3. Full Text On the estimation of transfer functions, regularizations and Gaussian processes—Revisited
by Chen, Tianshi and Ohlsson, Henrik and Ljung, Lennart and Reglerteknik and Linköpings universitet and Tekniska högskolan and Institutionen för systemteknik
Automatica, ISSN 0005-1098, 08/2012, Volume 48, Issue 8, pp. 1525 - 1535
Intrigued by some recent results on impulse response estimation by kernel and nonparametric techniques, we revisit the old problem of transfer function... 
Gaussian process | Transfer function estimation | Bias–variance trade-off | System identification | Bayesian inference | Regularization | Mean square error | Bias-variance trade-off | SELECTION | AUTOMATION & CONTROL SYSTEMS | ENGINEERING, ELECTRICAL & ELECTRONIC | Data banks | Mathematical analysis | Transfer functions | Impulse response | Mathematical models | Matrices | Bayesian analysis | Electrical Engineering, Electronic Engineering, Information Engineering | Reglerteknik | Teknik och teknologier | Information technology | TEKNIKVETENSKAP | Engineering and Technology | Elektroteknik och elektronik | Automatic control | Control Engineering | TECHNOLOGY | Informationsteknik
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4. Full Text Compositionally-warped Gaussian processes
by Rios, Gonzalo and Tobar, Felipe
Neural Networks, ISSN 0893-6080, 10/2019, Volume 118, pp. 235 - 246
The Gaussian process (GP) is a nonparametric prior distribution over functions indexed by time, space, or other high-dimensional index set. The GP is a... 
Function compositions | Non-Gaussian models | Gaussian process | Warped Gaussian processes | Neural networks | DENSITY-ESTIMATION | NEUROSCIENCES | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
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5. Full Text Gaussian processes for machine learning (GPML) toolbox
by Rasmussen, Carl Edward and Nickisch, Hannes
Journal of Machine Learning Research, ISSN 1532-4435, 11/2010, Volume 11, pp. 3011 - 3015
The GPML toolbox provides a wide range of functionality for Gaussian process (GP) inference and prediction. GPs are specified by mean and covariance functions;... 
Probabilistic regression and classification | Nonparametric bayes | Gaussian processes | CLASSIFICATION | nonparametric Bayes | AUTOMATION & CONTROL SYSTEMS | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | probabilistic regression and classification
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6. Full Text Fast Direct Methods for Gaussian Processes
by Ambikasaran, Sivaram and Foreman-Mackey, Daniel and Greengard, Leslie and Hogg, David W and O'Neil, Michael
IEEE Transactions on Pattern Analysis and Machine Intelligence, ISSN 0162-8828, 02/2016, Volume 38, Issue 2, pp. 252 - 265
A number of problems in probability and statistics can be addressed using the multivariate normal (Gaussian) distribution. In the one-dimensional case,... 
Symmetric matrices | evidence | direct solver | fast multipole method | Approximation methods | Matrix decomposition | Covariance matrices | covariance matrix | hierarchical off-diagonal low-rank | Gaussian process | likelihood | Gaussian processes | Acceleration | Kernel | Bayesian analysis | covariance function | determinant | Hierarchical off-diagonal low-rank | Ction | Direct solver | Determinant | Likelihood | Fast multipole method | Covariance matrix | FAST FOURIER-TRANSFORMS | APPROXIMATION | ALGORITHM | INTEGRAL-EQUATIONS | SOLVER | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC | Bayesian statistical decision theory | Usage | Analysis
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7. Full Text Gaussian Processes for Object Categorization
by Kapoor, Ashish and Kapoor, Ashish and Grauman, Kristen and Grauman, Kristen and Urtasun, Raquel and Urtasun, Raquel and Darrell, Trevor and Darrell, Trevor
International Journal of Computer Vision, ISSN 0920-5691, 6/2010, Volume 88, Issue 2, pp. 169 - 188
Discriminative methods for visual object category recognition are typically non-probabilistic, predicting class labels but not directly providing an estimate... 
Pattern Recognition | Gaussian process | Active learning | Kernel combination | Computer Science | Image Processing and Computer Vision | Computer Imaging, Vision, Pattern Recognition and Graphics | Artificial Intelligence (incl. Robotics) | Object recognition | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | Studies | Categories | Probability theory | Gaussian | Mathematical models | Probabilistic methods | Estimates | Recognition
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8. Full Text Anisotropic $$(2+1)$$ (2+1) d growth and Gaussian limits of q-Whittaker processes
by Borodin, Alexei and Borodin, Alexei and Corwin, Ivan and Corwin, Ivan and Ferrari, Patrik L and Ferrari, Patrik L
Probability Theory and Related Fields, ISSN 0178-8051, 10/2018, Volume 172, Issue 1, pp. 245 - 321
We consider a discrete model for anisotropic $$(2+1)$$ (2+1) -dimensional growth of an interface height function. Owing to a connection with q-Whittaker... 
2+1$$ 2 + 1 Growth models | Space–time process | percolation theory | Mathematical and Computational Biology | KPZ universality class | Theoretical, Mathematical and Computational Physics | statistical mechanics type models | Probability Theory and Stochastic Processes | Mathematics | Quantitative Finance | 60K35 Interacting random processes | 82C22 Interacting particle systems | q -Whittaker processes | Statistics for Business/Economics/Mathematical Finance/Insurance | Operations Research/Decision Theory | Gaussian free field | 60G15 Gaussian processes | q-Whittaker processes | 2 + 1 Growth models | UNIVERSALITY | PROBABILITY | DIRECTED POLYMERS | STATISTICS & PROBABILITY | Space-time process | 2+1 Growth models | Whittaker functions | Gaussian process | Partial differential equations | Anisotropy
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9. Full Text Choice modelling with Gaussian processes in the social sciences: A case study of neighbourhood choice in stockholm
by Mann, Richard P and Spaiser, Viktoria and Hedman, L.K and Sumpter, David J.T and Institutet för bostads- och urbanforskning (IBF) and Humanistisk-samhällsvetenskapliga vetenskapsområdet and Teknisk-naturvetenskapliga vetenskapsområdet and Uppsala universitet and Samhällsvetenskapliga fakulteten and Matematiska institutionen and Matematisk-datavetenskapliga sektionen and Tillämpad matematik och statistik
PLoS ONE, ISSN 1932-6203, 2018, Volume 13, Issue 11, p. e0206687
We present a non-parametric extension of the conditional logit model, using Gaussian process priors. The conditional logit model is used in quantitative social... 
DECISION | RANDOM REGRET MINIMIZATION | FLIGHT | DENSITY-ESTIMATION | BEHAVIOR | MULTIDISCIPLINARY SCIENCES | RISK | LOGIT | REPRODUCTION | PROSPECT-THEORY | Choice (Psychology) | Social sciences | Analysis | Gaussian processes | Economic models | Basis functions | Logit models | Households | Handbooks | Probability | Data processing | Housing | Minority & ethnic groups | Alternatives | Complexity | Case studies | Gaussian process | International conferences | Econometrics | Artificial intelligence | Samhällsvetenskap | Social och ekonomisk geografi | Social Sciences | Social and Economic Geography | Human Geography | Kulturgeografi
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10. Full Text Complex Gaussian Processes for Regression
by Boloix-Tortosa, Rafael and Murillo-Fuentes, Juan Jose and Payan-Somet, Francisco Javier and Perez-Cruz, Fernando
IEEE Transactions on Neural Networks and Learning Systems, ISSN 2162-237X, 11/2018, Volume 29, Issue 11, pp. 5499 - 5511
In this paper, we propose a novel Bayesian solution for nonlinear regression in complex fields. Previous solutions for kernels methods usually assume a... 
Training | Ground penetrating radar | Complex-valued processes | regression | Gaussian processes | Signal processing | Gaussian distribution | kernel methods | Covariance matrices | Kernel | Gaussian processes (GPs) | COMPUTER SCIENCE, HARDWARE & ARCHITECTURE | COMPUTER SCIENCE, THEORY & METHODS | KERNEL HILBERT-SPACES | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC | Gaussian process | Convolution | Covariance | Regression | Random processes | Equalization | Bayesian analysis
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11. Full Text Gaussian Process Morphable Models
by Luthi, Marcel and Gerig, Thomas and Jud, Christoph and Vetter, Thomas
IEEE Transactions on Pattern Analysis and Machine Intelligence, ISSN 0162-8828, 08/2018, Volume 40, Issue 8, pp. 1860 - 1873
Models of shape variations have become a central component for the automated analysis of images. An important class of shape models are point distribution... 
Deformable models | Analytical models | non-rigid registration | Shape | Computational modeling | Gaussian processes | Statistical shape modeling | Mathematical model | Kernel | image analysis | SEGMENTATION | REGISTRATION | ACTIVE SHAPE MODELS | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC | Computer vision | Parameter estimation | Medical imaging | Statistical analysis | Principal components analysis | Image segmentation | Image analysis | Gaussian process | Algorithms | Statistical models | Forearm | Normal distribution | Registration | Karhunen-Loeve expansion | Regularization | Three dimensional models | Statistical modelling | Multiscale methods
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12. Full Text Least squares estimator for non-ergodic Ornstein–Uhlenbeck processes driven by Gaussian processes
by El Machkouri, Mohamed and Es-Sebaiy, Khalifa and Ouknine, Youssef
Journal of the Korean Statistical Society, ISSN 1226-3192, 09/2016, Volume 45, Issue 3, pp. 329 - 341
The statistical analysis for equations driven by fractional Gaussian process (fGp) is relatively recent. The development of stochastic calculus with respect to... 
Parameter estimation | Non-ergodic Gaussian Ornstein–Uhlenbeck process | Non-ergodic Gaussian Ornstein-Uhlenbeck process | STATISTICS & PROBABILITY | Brownian motion | Models | Analysis | Gaussian processes | Least squares | Probability | Mathematics
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13. Full Text GPstuff: Bayesian modeling with Gaussian processes
by Vanhatalo, J and Riihimaki, J and Hartikainen, J and Jylänki, P.P and Tolvanen, V and Vehtari, A
Journal of Machine Learning Research, ISSN 1532-4435, 2013, Volume 14, Issue 1, pp. 1175 - 1179
The GPstuff toolbox is a versatile collection of Gaussian process models and computational tools required for Bayesian inference. The tools include, among... 
Bayesian hierarchical model | Gaussian process | nonparametric Bayes | AUTOMATION & CONTROL SYSTEMS | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | Nonparametric bayes
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14. Full Text Gaussian processes for time-series modelling
by Roberts, S and Osborne, M and Ebden, M and Reece, S and Gibson, N and Aigrain, S
Philosophical Transactions of the Royal Society A, ISSN 1364-503X, 02/2013, Volume 371, Issue 1984, p. 20110550
In this paper, we offer a gentle introduction to Gaussian processes for time-series data analysis. The conceptual framework of Bayesian modelling for... 
MATHEMATICS | applied mathematics | mathematical modelling | COMPUTER SCIENCE | Articles | statistics | pattern recognition | Bayesian modelling | Time-series analysis | Gaussian processes | MULTIDISCIPLINARY SCIENCES | time-series analysis
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15. Full Text Gaussian Processes for Data-Efficient Learning in Robotics and Control
by Deisenroth, Marc Peter and Fox, Dieter and Rasmussen, Carl Edward
IEEE Transactions on Pattern Analysis and Machine Intelligence, ISSN 0162-8828, 02/2015, Volume 37, Issue 2, pp. 408 - 423
Autonomous learning has been a promising direction in control and robotics for more than a decade since data-driven learning allows to reduce the amount of... 
Uncertainty | Computational modeling | Predictive models | robotics | Probabilistic logic | control | Approximation methods | Policy search | reinforcement learning | Gaussian processes | Data models | Bayesian inference | Robots | Control | Robotics | Reinforcement learning | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC | Usage | Distribution (Probability theory) | Machine learning | Innovations
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16. Full Text Twin Gaussian Processes for Structured Prediction
by Bo, Liefeng and Bo, Liefeng and Sminchisescu, Cristian and Sminchisescu, Cristian
International Journal of Computer Vision, ISSN 0920-5691, 3/2010, Volume 87, Issue 1, pp. 28 - 52
We describe twin Gaussian processes (TGP), a generic structured prediction method that uses Gaussian process (GP) priors on both covariates and responses, both... 
Pattern Recognition | Video processing | Computer Science | Image Processing and Computer Vision | Computer Imaging, Vision, Pattern Recognition and Graphics | Gaussian processes | Artificial Intelligence (incl. Robotics) | 3d human pose reconstruction | Feature extraction | Structured prediction | 3d human pose reconstruction | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | Studies | Availability | Human | Training | Mathematical analysis | Markers | Gaussian | Mathematical models | Calibration
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17. Full Text Extended Target Tracking Using Gaussian Processes
by Wahlstrom, Niklas and Ozkan, Emre and Reglerteknik and Linköpings universitet and Tekniska fakulteten and Institutionen för systemteknik
IEEE Transactions on Signal Processing, ISSN 1053-587X, 08/2015, Volume 63, Issue 16, pp. 4165 - 4178
In this paper, we propose using Gaussian processes to track an extended object or group of objects, that generates multiple measurements at each scan. The... 
Target tracking | Shape | Computational modeling | Extended target tracking | Gaussian processes | Kinematics | Position measurement | Noise measurement | star-convex | FILTER | ENGINEERING, ELECTRICAL & ELECTRONIC | Usage | Computer-generated environments | Computer simulation | Analysis | Confidence intervals | Algorithms | Tracking | Regression | Gaussian | Gating and risering | State estimation | Teknik och teknologier | Engineering and Technology | Elektroteknik och elektronik | Electrical Engineering, Electronic Engineering, Information Engineering | Extended target tracking; Gaussian processes; star-convex
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18. Full Text Improved process monitoring based on global–local manifold analysis and statistical local approach for industrial process
by Zhan, Chengjun and Li, Shuanghong and Yang, Yupu
Journal of Process Control, ISSN 0959-1524, 03/2019, Volume 75, pp. 107 - 119
•A novel process monitoring method based on manifold analysis and statistical local approach is proposed.•Two augmented vectors based on eigenvectors that... 
Fault diagnosis | Statistical local approach | Fault detection | Gaussian assumption | Global–local manifold analysis | DIAGNOSIS | DIMENSIONALITY REDUCTION | MODEL | PCA | Global-local manifold analysis | ENGINEERING, CHEMICAL | PROJECTION | FAULT-DETECTION | SELECTION | AUTOMATION & CONTROL SYSTEMS | Control systems | Algorithms | Analysis | Production processes | Innovations
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19. Full Text Wind Power Forecasts Using Gaussian Processes and Numerical Weather Prediction
by Niya Chen and Zheng Qian and Nabney, Ian T and Xiaofeng Meng
IEEE Transactions on Power Systems, ISSN 0885-8950, 03/2014, Volume 29, Issue 2, pp. 656 - 665
Since wind at the earth's surface has an intrinsically complex and stochastic nature, accurate wind power forecasts are necessary for the safe and economic use... 
Censored data | Gaussian process | Wind speed | Atmospheric modeling | numerical weather prediction | Predictive models | Wind power generation | Data models | Wind forecasting | wind power forecasting | ARTIFICIAL NEURAL-NETWORKS | ENGINEERING, ELECTRICAL & ELECTRONIC | Usage | Numerical analysis | Neural networks | Stochastic processes | Innovations | Gaussian processes | Electric power systems | Wind power | Meteorology | Weather | Training | Climatology | Economic forecasting | Mathematical models | Learning theory
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20. Full Text EFFICIENT SIMULATION OF BROWN-RESNICK PROCESSES BASED ON VARIANCE REDUCTION OF GAUSSIAN PROCESSES
by Oesting, M and Strokorb, K
ADVANCES IN APPLIED PROBABILITY, ISSN 0001-8678, 12/2018, Volume 50, Issue 4, pp. 1155 - 1175
Brown-Resnick processes are max-stable processes that are associated to Gaussian processes. Their simulation is often based on the corresponding spectral... 
Gaussian process | variance reduction | max-stable process | spatial extremes | Brown-Resnick process | simulation | EXTREMES | ISOTROPIC CORRELATION-FUNCTIONS | variogram | STATISTICS & PROBABILITY | Mathematical problems | Domains | Algorithms | Simulation | Computer simulation | Representations
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