Robuta

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Jul 13, 2025 - Scalable Bayesian Inference in the Era of Deep Learning: From Gaussian Processes to Deep Neural Networks by Javier Antoran First submitted to arxiv on: 29 Apr 2 bayesian inferencethe eradeep learninggaussian processessummary https://www.tcs.tifr.res.in/web/events/1656 Sparsifying suprema of Gaussian processes gaussian processessuprema https://osuva.uwasa.fi/items/5a5a3277-7a4d-41c0-a4e6-9664d8fc193c Fredholm representation of multi-parameter Gaussian processes with applications to equivalence in... We show that every multiparameter Gaussian process with integrable variance function admits a Wiener integral representation of Fredholm type with respect to... gaussian processesrepresentationmultiparameterapplications https://researchr.org/publication/XiangNZZ16 Collusion-resistant Spatial Phenomena Crowdsourcing via Mixture of Gaussian Processes Regression -... gaussian processescollusionresistantspatialphenomena https://aaltodoc.aalto.fi/items/98faca34-e405-4ed0-9c84-8cd6178d8b20 Approximate state-space Gaussian processes via spectral transformation State-space representations of Gaussian process regression use Kalman filtering and smoothing theory to downscale the computational complexity of the... gaussian processesapproximatestatespacevia https://aclanthology.org/D14-1190/ Joint Emotion Analysis via Multi-task Gaussian Processes - ACL Anthology Daniel Beck, Trevor Cohn, Lucia Specia. Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP). 2014. emotion analysisgaussian processesjointviamulti https://repository.mines.edu/entities/publication/711c6f59-a25b-4f50-bb5a-65833c699334 Quantitative assessment of metabolic health using dynamical systems informed by Gaussian processes As glucose enters the bloodstream after a meal, the beta cells of the pancreas release the hormone insulin to signal glucose uptake by tissues throughout the... metabolic healthdynamical systemsgaussian processesquantitativeassessment https://khazna.ku.ac.ae/en/publications/understanding-smoothness-of-vector-gaussian-processes-on-product-/ Understanding Smoothness of Vector Gaussian Processes on Product Spaces - Khalifa University gaussian processesunderstandingsmoothnessvectorproduct https://www.catalyzex.com/paper/a-framework-for-nonstationary-gaussian A Framework for Nonstationary Gaussian Processes with Neural Network Parameters A Framework for Nonstationary Gaussian Processes with Neural Network Parameters: Paper and Code. Gaussian processes have become a popular tool for... gaussian processesneural networkframeworkparameters https://api.deepai.org/publication/nonstationary-multivariate-gaussian-processes-for-electronic-health-records Nonstationary Multivariate Gaussian Processes for Electronic Health Records | DeepAI Oct 13, 2019 - 10/13/19 - We propose multivariate nonstationary Gaussian processes for jointly modeling multiple clinical variables, where the key parameter... electronic health recordsgaussian processesdeepai https://arxiv.org/abs/1810.03052 [1810.03052] Deep convolutional Gaussian processes Abstract page for arXiv paper 1810.03052: Deep convolutional Gaussian processes gaussian processesdeep https://uwspace.uwaterloo.ca/items/32d68807-97a8-4b7a-bae6-36a8184eb34e Planning Under Uncertainty: Informative and Stochastic Path Planning via Gaussian Processes Autonomous systems operating in real-world environments often face uncertainty due to incomplete or noisy information about their surroundings. Effective... gaussian processesplanninguncertaintyinformativestochastic https://vivo.colorado.edu/display/pubid_306909 Nonrigid Registration Using Gaussian Processes and Local Likelihood Estimation | CU Experts | CU... gaussian processesregistrationusinglocallikelihood https://www.deisenroth.cc/publication/deisenroth-2015-b/ Distributed Gaussian Processes | Marc Deisenroth gaussian processesmarc deisenrothdistributed https://www.th-owl.de/elsa/record/12812 Towards Gaussian Processes for Automatic and Interpretable Anomaly Detection in Industry 4.0 gaussian processesanomaly detectionin industrytowardsautomatic https://impact.ornl.gov/en/publications/comparison-between-gaussian-processes-and-dmd-surrogates-for-isot/ Comparison between Gaussian processes and DMD surrogates for isotopic composition prediction - Oak... gaussian processescomparisondmdsurrogatescomposition https://openreview.net/forum?id=FwVmM8Zol_8 Vector-valued Gaussian Processes on Riemannian Manifolds via Gauge Independent Projected Kernels |... Vector-valued Gaussian Processes on Riemannian Manifolds via Gauge Independant Projected Kernels gaussian processesvectorvaluedmanifoldsvia https://is.mpg.de/publications/wengeretal22b Posterior and Computational Uncertainty in Gaussian Processes | MPI-IS Our goal is to understand the principles of Perception, Action and Learning in autonomous systems that successfully interact with complex environments and to... gaussian processesposteriorcomputationaluncertaintympi https://orbi.uliege.be/handle/2268/131334 ORBi: Decoding spontaneous brain activity from fMRI using Gaussian Processes: tracking brain... brain activitygaussian processesorbidecodingspontaneous https://jmlr.org/papers/v22/21-0072.html A general linear-time inference method for Gaussian Processes on one dimension gaussian processeson onegenerallineartime https://www.ijsrp.org/research-paper-0717.php?rp=P676589 New Kernel Function in Gaussian Processes Model New Kernel Design Technique was presented in the form of the sum of Linear Kernel, the multiplication of 3 Kernel Functions, including Squared Exponential... gaussian processesnewkernelfunctionmodel https://calbridge.org/my_keywords/time-series-modeling-using-gaussian-processes/ Time series modeling using Gaussian Processes - Calbridge Professor: Dongwook Lee Description: The project will explore numerical approaches to modeling time series data when solving ordinary differential equations.... time seriesgaussian processesmodelingusingcalbridge https://iq.opengenus.org/intuitive-introduction-to-gaussian-process/ Intuitive Introduction to Gaussian Processes Sep 14, 2019 - Gaussian Process is a non-parametric model that can be used to represent a distribution over functions. introduction togaussian processesintuitive https://www.cs.cit.tum.de/en/sccs/news/news/article/martin-klapacz-multifidelity-gaussian-processes-for-uncertainty-quantification/ Martin Klapacz: Multifidelity Gaussian Processes for Uncertainty Quantification - Chair of... gaussian processesuncertainty quantificationmartinchair https://www.dagstuhl.de/en/seminars/seminar-calendar/seminar-details/16481 Dagstuhl Seminar 16481: New Directions for Learning with Kernels and Gaussian Processes dagstuhl seminarnew directionsfor learninggaussian processeskernels https://theclimatelink.org/gaussian-processes/ Gaussian Processes | Global Climate Research Portal gaussian processesglobal climateresearch portal https://scholars.duke.edu/publication/1048104 Scholars@Duke publication: Mechanistic Hierarchical Gaussian Processes. gaussian processesscholarsdukepublicationmechanistic https://pubmed.ncbi.nlm.nih.gov/37769241/ An improved rhythmicity analysis method using Gaussian Processes detects cell-density dependent... ODeGP is available at https://github.com/Shaonlab/ODeGP. gaussian processescell densityimprovedanalysismethod https://babel.isa.uma.es/kipr/?p=1155 A kind of reinforcement learning that decouples modelling from planning using Gaussian Processes... kind ofreinforcement learninggaussian processesmodellingplanning https://k4all.org/2010/08/gaussian-processes-for-machine-learning-toolbox-3-0/ Gaussian Processes for Machine Learning Toolbox 3.0 | Knowledge 4 All Foundation Ltd. gaussian processesmachine learningall foundationtoolboxknowledge https://kuscholarworks.ku.edu/entities/publication/9095de5d-2c90-45e7-a7f6-b13dd4a4eae8 Hitting Times for Gaussian Processes See article for abstract. gaussian processeshittingtimes https://researchconnect.stonybrook.edu/en/publications/cardiotocography-analysis-by-empirical-dynamic-modeling-and-gauss/ Cardiotocography analysis by empirical dynamic modeling and Gaussian processes - Stony Brook... gaussian processesstony brookanalysisempiricaldynamic https://www.jstatsoft.org/article/view/v019i02 Bayesian Smoothing with Gaussian Processes Using Fourier Basis Functions in the spectralGP Package... gaussian processesbayesiansmoothingusingfourier https://uwcscholar.uwc.ac.za/items/93f59499-f9d7-45c0-973f-ad6f8d6f3788 Using sparse gaussian processes for predicting robust inertial confinement fusion implosion yields Here we present the application of an advanced Sparse Gaussian Process based machine learning algorithm to the challenge of predicting the yields of inertial... gaussian processesusingsparserobustinertial https://www.proceedings.com/079017-2148.html HHD-GP: Incorporating Helmholtz-Hodge Decomposition into Gaussian Processes for Learning Dynamical... The world's premier source for conference proceedings, offering Print-on-Demand, DOI, and Content Hosting services. gaussian processesfor learninghhdgpincorporating https://bytez.com/docs/arxiv/1807.02537/paper Fully Scalable Gaussian Processes using Subspace Inducing Inputs | Read Paper on Bytez Jul 6, 2018 - We introduce fully scalable Gaussian processes, an implementation scheme that tackles the problem of treating a high number of training instances together with... fully scalablegaussian processesread paperusingsubspace https://indico.nikhef.nl/event/4875/contributions/20443/ EuCAIFCon 2024 (April 30, 2024 - May 3, 2024): Gaussian processes for managing model uncertainty in... Note: This indico page is used for handling abstract submission. To register for the conference please go to the EuCAIFCon24 registration website. Conference... gaussian processesaprilmaymanagingmodel https://www.frontiersin.org/journals/bioengineering-and-biotechnology/articles/10.3389/fbioe.2022.1057807/full Frontiers | Cardiotocography analysis by empirical dynamic modeling and Gaussian processes During labor, fetal heart rate (FHR) and uterine activity (UA) can be continuously monitored using Cardiotocography (CTG). 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