Papers
1,854 papers found
Meta-Weighted Gaussian Process Experts for Personalized Forecasting of AD Cognitive Changes
Ognjen (Oggi) Rudovic, Yuria Utsumi, Ricardo Guerrero et al.
Exact Inference on Conditional Linear Γ-Gaussian Bayesian Networks
Ivar Simonsson, Petter Mostad
Differential networking with path weights in Gaussian trees
Alberto Roverato, Robert Castelo
Gaussian Sum-Product Networks Learning in the Presence of Interval Censored Data
Clavier Pierre, Bouaziz Olivier, Nuel Gregory
Lifted Query Answering in Gaussian Bayesian Networks
Mattis Hartwig, Ralf Möller
Missing Values in Multiple Joint Inference of Gaussian Graphical Models
Veronica Tozzo, Davide Garbarino, Annalisa Barla
Online Updating of Conditional Linear Gaussian Bayesian Networks
Anders L Madsen, Kristian G Olesen, Frank Jensen et al.
Model inclusion lattice of coloured Gaussian graphical models for paired data
Alberto Roverato, Dung Ngoc Nguyen
Gaussian Processes for Signal Strength-Based Location Estimation
B. Ferris, D. Haehnel, D. Fox
Gaussian Beam Processes: A Nonparametric Bayesian Measurement Model for Range Finders
Christian Plagemann, Kristian Kersting, Patrick Pfaff et al.
Gas Distribution Modeling using Sparse Gaussian Process Mixture Models
Cyrill Stachniss, Christian Plagemann, Achim Lilienthal et al.
Learning GP-BayesFilters via Gaussian process latent variable models
J. Ko and D. Fox
Distributed Approximation of Joint Measurement Distributions Using Mixtures of Gaussians
Brian Julian, Stephen Smith, Daniela Rus
The Banana Distribution is Gaussian: A Localization Study with Exponential Coordinates
Andrew Long, Kevin Wolfe, Michael Mashner et al.
Batch Continuous-Time Trajectory Estimation as Exactly Sparse Gaussian Process Regression
Tim Barfoot, Chi Hay Tong, Simo Sarkka
A New Perspective and Extension of the Gaussian Filter
Manuel Wuthrich, Sebastian Trimpe, Daniel Kappler et al.
Motion Planning as Probabilistic Inference using Gaussian Processes and Factor Graphs
Jing Dong, Mustafa Mukadam, Frank Dellaert et al.
Real-Time Information-Theoretic Exploration with Gaussian Mixture Model Maps
Wennie Tabib, Kshitij Goel, John Yao et al.
Active Preference-Based Gaussian Process Regression for Reward Learning
Erdem Biyik, Nicolas Huynh, Mykel Kochenderfer et al.
Autonomous Navigation, Mapping and Exploration with Gaussian Processes
Mahmoud Ali, Hassan Jardali, Nicholas Roy et al.
Computation-Aware Learning for Stable Control with Gaussian Process
Wenhan Cao, Alexandre Capone, Rishabh Yadav et al.
PINGS: Gaussian Splatting Meets Distance Fields within a Point-Based Implicit Neural Map
Yue Pan, Xingguang Zhong, Liren Jin et al.
Novel Demonstration Generation with Gaussian Splatting Enables Robust One-Shot Manipulation
Sizhe Yang, Wenye Yu, Jia Zeng et al.
GM-CTSC at SemEval-2020 Task 1: Gaussian Mixtures Cross Temporal Similarity Clustering
Pierluigi Cassotti, Annalina Caputo, Marco Polignano et al.