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https://www.mathworks.com/help/stats/classreg.learning.regr.compactregressiongp.html CompactRegressionGP - Compact Gaussian process regression model class - MATLAB CompactRegressionGP is a compact Gaussian process regression (GPR) model. gaussian process regression compact model class matlab https://arxiv.org/abs/2005.03770 [2005.03770] Planning from Images with Deep Latent Gaussian Process Dynamics Abstract page for arXiv paper 2005.03770: Planning from Images with Deep Latent Gaussian Process Dynamics gaussian process 2005 03770 planning images https://openreview.net/forum?id=Z8QlQ207V6 Markovian Gaussian Process Variational Autoencoders | OpenReview Sequential VAEs have been successfully considered for many high-dimensional time series modelling problems, with many variant models relying on discrete-time... gaussian process variational autoencoders markovian openreview https://jmlr.org/papers/v26/22-0828.html Relaxed Gaussian Process Interpolation: a Goal-Oriented Approach to Bayesian Optimization gaussian process goal oriented relaxed interpolation https://research.google/pubs/density-based-user-representation-through-gaussian-process-regression-for-multi-interest-personalized-retrieval/ Density-based User Representation through Gaussian Process Regression for Multi-interest... gaussian process regression density based user representation https://www.osti.gov/pages/biblio/1608212-imaging-mechanism-hyperspectral-scanning-probe-microscopy-via-gaussian-process-modelling Imaging mechanism for hyperspectral scanning probe microscopy via Gaussian process modelling... The U.S. Department of Energy's Office of Scientific and Technical Information scanning probe microscopy gaussian process imaging mechanism hyperspectral https://jmlr.org/papers/v22/21-0853.html Consistency of Gaussian Process Regression in Metric Spaces gaussian process regression consistency metric spaces https://observablehq.com/@herbps10/gaussian-processes?collection=@herbps10/probability-distributions Gaussian Process Playground / Herb Susmann | Observable Feb 8, 2022 - Let be a stochastic process indexed by . is called a Gaussian Process if any finite set of realizations of the process at points are multivariate normally... gaussian process playground herb observable https://deepai.org/publication/real-time-informative-surgical-skill-assessment-with-gaussian-process-learning Real-time Informative Surgical Skill Assessment with Gaussian Process Learning | DeepAI Dec 5, 2021 - 12/05/21 - Endoscopic Sinus and Skull Base Surgeries (ESSBSs) is a challenging and potentially dangerous surgical procedure, and objective sk... real time skill assessment gaussian process informative surgical https://openreview.net/forum?id=8xAHeICO69 Improving Hyperparameter Learning under Approximate Inference in Gaussian Process Models |... Approximate inference in Gaussian process (GP) models with non-conjugate likelihoods gets entangled with the learning of the model hyperparameters. We improve... approximate inference gaussian process improving hyperparameter learning https://jmlr.org/papers/v16/neumann15a.html pyGPs -- A Python Library for Gaussian Process Regression and Classification gaussian process regression python library classification https://gaussianprocess.org/ Welcome to the Gaussian Process pages | the Gaussian Process web site This web site aims to provide an overview of resources concerned with probabilistic modeling, inference and learning based on Gaussian processes. welcome to the gaussian process pages web site https://openreview.net/forum?id=r1s0gx3iG One-class Gaussian process regressor for quality assessment of transperineal ultrasound images |... The use of ultrasound guidance in prostate cancer radiotherapy workflows is not widespread. This can be partially attributed to the need for image... gaussian process https://www.slideserve.com/lforehand/propagating-uncertainty-in-pomdp-value-iteration-with-gaussian-process-powerpoint-ppt-presentation PPT - Propagating Uncertainty In POMDP Value Iteration with Gaussian Process PowerPoint... Propagating Uncertainty In POMDP Value Iteration with Gaussian Process. Written by Eric Tuttle and Zoubin Ghahramani Presenter by Hui Li May 20, 2005. Outline:... value iteration gaussian process ppt propagating uncertainty https://arxiv.org/abs/1701.09055 [1701.09055] A Gaussian Process Regression Model for Distribution Inputs Abstract page for arXiv paper 1701.09055: A Gaussian Process Regression Model for Distribution Inputs gaussian process regression for distribution 1701 09055 model https://deepai.org/publication/gaussian-process-landmarking-on-manifolds Gaussian Process Landmarking on Manifolds | DeepAI Feb 9, 2018 - 02/09/18 - As a means of improving analysis of biological shapes, we propose a greedy algorithm for sampling a Riemannian manifold based on t... gaussian process manifolds deepai https://www.jmp.com/support/help/14/gaussian-process-imse-optimal-designs.shtml Gaussian Process IMSE Optimal Designs The Gaussian process IMSE optimal design method constructs designs that are suitable for Gaussian process models. Gaussian process models fit a wide variety of... gaussian process optimal designs https://www.umass.edu/mathematics-statistics/events/lulu-kang-tutorial-gaussian-process-and-bayesian-optimization Lulu Kang: Tutorial on Gaussian Process and Bayesian Optimization : Department of Mathematics and... In this tutorial, I will give an overview and brief introduction to the following topics: Gaussian process regression, Design of experiments for GP models,... gaussian process https://deepai.org/publication/gaussian-process-gradient-maps-for-loop-closure-detection-in-unstructured-planetary-environments Gaussian Process Gradient Maps for Loop-Closure Detection in Unstructured Planetary Environments |... Sep 1, 2020 - 09/01/20 - The ability to recognize previously mapped locations is an essential feature for autonomous systems. Unstructured planetary-like e... gaussian process for loop https://openreview.net/forum?id=v1bxRZJ9c8V&referrer=%5Bthe%20profile%20of%20%C3%87a%C4%9Fatay%20Y%C4%B1ld%C4%B1z%5D(%2Fprofile%3Fid%3D~%C3%87a%C4%9Fatay_Y%C4%B1ld%C4%B1z1) Learning interacting dynamical systems with latent Gaussian process ODEs | OpenReview Modeling interacting dynamical systems with latent Gaussian process ODEs leads to disentangled representations and improved calibration. dynamical systems gaussian process learning interacting latent https://jmlr.org/papers/v14/chalupka13a.html A Framework for Evaluating Approximation Methods for Gaussian Process Regression gaussian process framework evaluating approximation methods https://www.jmlr.org/papers/v26/22-0828.html Relaxed Gaussian Process Interpolation: a Goal-Oriented Approach to Bayesian Optimization gaussian process goal oriented relaxed interpolation https://openreview.net/forum?id=fnsLhSwS8e&referrer=%5Bthe%20profile%20of%20Kwang%20In%20Kim%5D(%2Fprofile%3Fid%3D~Kwang_In_Kim1) Active Deep Learning Guided by Efficient Gaussian Process Surrogates | OpenReview The success of active learning relies on the exploration of the underlying data-generating distributions, populating sparsely labeled data areas, and... deep learning gaussian process active guided efficient https://www.preprints.org/manuscript/202211.0428 Reducing the Complexity of Musculoskeletal Models using Gaussian Process Emulators[v1] |... Musculoskeletal models (MSKMs) are used to estimate the muscle and joint forces involved in human locomotion, often associated with the onset of degenerative... gaussian process reducing complexity musculoskeletal https://jmlr.org/papers/v24/19-094.html Multi-view Collaborative Gaussian Process Dynamical Systems multi view gaussian process collaborative dynamical systems https://jmlr.org/papers/v18/16-603.html A Unifying Framework for Gaussian Process Pseudo-Point Approximations using Power Expectation... gaussian process https://www.frontiersin.org/journals/earth-science/articles/10.3389/feart.2022.944301/full Frontiers | Sparse Gaussian Process Regression for Landslide Displacement Time-Series Forecasting Landslide hazards are complex nonlinear systems with a highly dynamic nature. Accurate forecasting of landslide displacement and evolution is crucial for the... gaussian process regression time series frontiers sparse https://gpflow.org/ GPflow - Build Gaussian process models in python GPflow is a package for building Gaussian process models in python, using TensorFlow. It was originally created and is now managed by James Hensman and... gaussian process build models python https://openreview.net/forum?id=lCYrsdHb5SQ&referrer=%5Bthe%20profile%20of%20Simon%20J.%20Godsill%5D(%2Fprofile%3Fid%3D~Simon_J._Godsill1) Non-Gaussian Process Regression | OpenReview We extend the Gaussian process regression model to allow for locally adaptive behaviour through time-changed GPs and learn latent probabilistic representations... gaussian process regression non openreview https://openreview.net/forum?id=RUkMMpiSbM Uncovering Neural Encoding Variability with Infinite Gaussian Process Factor Analysis | OpenReview Gaussian Process Factor Analysis (GPFA) is a powerful factor analysis model for extracting low-dimensional latent processes underlying population neural... neural encoding gaussian process factor analysis uncovering variability https://www.umass.edu/mathematics-statistics/events/generalized-variable-selection-algorithms-gaussian-process-models Generalized Variable Selection Algorithms for Gaussian Process Models : Department of Mathematics... With the rapid development of modern technology, massive amounts of data with complex pattern are generated. Gaussian process models that can easily fit the... variable selection gaussian process department of generalized algorithms https://gpflow.org/index.html GPflow - Build Gaussian process models in python GPflow is a package for building Gaussian process models in python, using TensorFlow. It was originally created and is now managed by James Hensman and... gaussian process build models python https://openreview.net/forum?id=hYxZJycvrz Integration-free Kernels for Equivariant Gaussian Process Modelling | OpenReview We study the incorporation of equivariances into vector-valued GPs and more general classes of random field models. While kernels guaranteeing equivariances... gaussian process integration free kernels equivariant https://openreview.net/forum?id=oUZ5JweNRc Response Time Improves Gaussian Process Models for Perception and Preferences | OpenReview Models for human choice prediction in preference learning and perception science often use binary response data, requiring many samples to accurately learn... response time gaussian process improves https://aclanthology.org/W19-4732/ Gaussian Process Models of Sound Change in Indo-Aryan Dialectology - ACL Anthology Chundra Cathcart. Proceedings of the 1st International Workshop on Computational Approaches to Historical Language Change. 2019. gaussian process sound change https://www.sintef.no/en/publications/publication/0198cc66f92a-04cb8ce5-c732-4f58-97be-a1833fa84b7c/ PIGPVAE: physics-informed gaussian process variational autoencoders - SINTEF gaussian process variational autoencoders physics informed sintef https://jmlr.org/papers/v26/22-0973.html Mixtures of Gaussian Process Experts with SMC^2 mixtures of gaussian process experts smc 2 https://arxiv.org/abs/2206.05608 [2206.05608] Gradient Boosting Performs Gaussian Process Inference Abstract page for arXiv paper 2206.05608: Gradient Boosting Performs Gaussian Process Inference gradient boosting gaussian process 2206 05608 performs https://openreview.net/forum?id=Ohxy3YFsUm Variational Inference with Censored Gaussian Process Regressors | OpenReview We consider the problem of Bayesian inference when some observations have been censored. In censored data, the dependent variable has been clipped, so we only... variational inference gaussian process censored regressors openreview https://openreview.net/forum?id=KQ5jI19kF3 Optimistic Optimization of Gaussian Process Samples | OpenReview Bayesian optimization is a popular formalism for global optimization, but its computational costs limit it to expensive-to-evaluate functions. A competing,... gaussian process optimistic optimization samples openreview https://openreview.net/forum?id=zUiH8UUYDo Scalable Deep Kernel Gaussian Process for Vehicle Dynamics in Autonomous Racing | OpenReview In this work, we have proven that DKL-SKIP, as a scalable deep kernel learning for Gaussian Process, is a promising tool for modeling complex vehicle dynamics... gaussian process https://deepai.org/publication/misspecified-gaussian-process-bandit-optimization Misspecified Gaussian Process Bandit Optimization | DeepAI Nov 9, 2021 - 11/09/21 - We consider the problem of optimizing a black-box function based on noisy bandit feedback. Kernelized bandit algorithms have shown... gaussian process bandit optimization deepai https://www.aanda.org/articles/aa/full_html/2025/07/aa54518-25/aa54518-25.html gallifrey: JAX-based Gaussian process structure learning for astronomical time series | Astronomy &... gaussian process structure learning https://jmlr.org/papers/v14/riihimaki13a.html Nested Expectation Propagation for Gaussian Process Classification with a Multinomial Probit... expectation propagation gaussian process nested https://gpss.cc/ About | Gaussian Process Summer Schools Gaussian process summer schools teach the theory and practice of Gaussian processes. This site gives details of schools past and present. gaussian process summer schools https://deepai.org/publication/gaussian-process-bandit-optimization-of-the-thermodynamic-variational-objective Gaussian Process Bandit Optimization of the Thermodynamic Variational Objective | DeepAI Oct 29, 2020 - 10/29/20 - Achieving the full promise of the Thermodynamic Variational Objective (TVO), a recently proposed variational lower bound on the lo... gaussian process of the bandit optimization thermodynamic https://www.jmlr.org/beta/papers/v24/21-0556.html Posterior Contraction for Deep Gaussian Process Priors gaussian process posterior contraction deep priors https://www.osti.gov/biblio/1887418 Monotonic Gaussian Process for Physics-Constrained Machine Learning With Materials Science... Physics-constrained machine learning is emerging as an important topic in the field of machine learning for physics. One of the most significant advantages of... gaussian process machine learning monotonic physics https://arxiv.org/abs/1406.7343 [1406.7343] Hierarchical Nearest-Neighbor Gaussian Process Models for Large Geostatistical Datasets Abstract page for arXiv paper 1406.7343: Hierarchical Nearest-Neighbor Gaussian Process Models for Large Geostatistical Datasets nearest neighbor gaussian process https://openreview.net/forum?id=o1woLLxcpv Implications of Gaussian process kernel mismatch for out-of-distribution data | OpenReview Gaussian processes provide reliable uncertainty estimates in nonlinear modeling, but a poor choice of the kernel can lead to poor generalization. Although... gaussian process implications kernel https://arxiv.org/abs/2510.15486 [2510.15486] A Hybrid Quantum Solver for Gaussian Process Regression Abstract page for arXiv paper 2510.15486: A Hybrid Quantum Solver for Gaussian Process Regression gaussian process 2510 hybrid quantum solver https://www.jmlr.org/papers/v22/20-662.html Convergence Guarantees for Gaussian Process Means With Misspecified Likelihoods and Smoothness gaussian process convergence guarantees https://openreview.net/forum?id=xt4oAjRL7g Robust Transfer Learning for Active Level Set Estimation with Locally Adaptive Gaussian Process... The objective of active level set estimation for a black-box function is to precisely identify regions where the function values exceed or fall below a... https://arxiv.org/abs/1510.07130 [1510.07130] Non-separable Dynamic Nearest-Neighbor Gaussian Process Models for Large... Abstract page for arXiv paper 1510.07130: Non-separable Dynamic Nearest-Neighbor Gaussian Process Models for Large spatio-temporal Data With an Application to... nearest neighbor https://openreview.net/forum?id=KeI9E-gsoB Learning Curves for Gaussian Process Regression with Power-Law Priors and Targets | OpenReview We characterize the power-law asymptotics of learning curves for Gaussian process regression (GPR) under the assumption that the eigenspectrum of the prior and... gaussian process regression https://midigap.cs.uni-freiburg.de/ The Unreasonable Effectiveness of Discrete-Time Gaussian Process Mixtures for Robot Policy Learning https://arxiv.org/abs/2510.01840 [2510.01840] A reproducible comparative study of categorical kernels for Gaussian process... Abstract page for arXiv paper 2510.01840: A reproducible comparative study of categorical kernels for Gaussian process regression, with new clustering-based... comparative study https://github.com/SheffieldML/gprege GitHub - SheffieldML/gprege: Gaussian process software in R and Matlab for detecting quiet genes.... Gaussian process software in R and Matlab for detecting quiet genes. From Alfredo Kalaitzis's thesis work. - SheffieldML/gprege https://arxiv.org/abs/1408.4660 [1408.4660] Joint Hierarchical Gaussian Process Model with Application to Forecast in Medical... Abstract page for arXiv paper 1408.4660: Joint Hierarchical Gaussian Process Model with Application to Forecast in Medical Monitoring https://openreview.net/forum?id=rzsDn7Vzxf The Gaussian Neural Process | OpenReview Neural Processes (NPs; Garnelo et al., 2018a,b) are a rich class of models for meta-learning that map data sets directly to predictive stochastic processes. We... gaussian neural process openreview https://arxiv.org/abs/2509.02571 [2509.02571] Gaussian Process Regression of Steering Vectors With Physics-Aware Deep Composite... Abstract page for arXiv paper 2509.02571: Gaussian Process Regression of Steering Vectors With Physics-Aware Deep Composite Kernels for Augmented Listening gaussian process regression https://arxiv.org/abs/1906.03564 [1906.03564] A Low Rank Gaussian Process Prediction Model for Very Large Datasets Abstract page for arXiv paper 1906.03564: A Low Rank Gaussian Process Prediction Model for Very Large Datasets