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State Space Gaussian Processes with Non-Gaussian Likelihood
v1v2v3v4v5 (latest)

State Space Gaussian Processes with Non-Gaussian Likelihood

13 February 2018
H. Nickisch
Arno Solin
A. Grigorevskiy
    GP
ArXiv (abs)PDFHTML

Papers citing "State Space Gaussian Processes with Non-Gaussian Likelihood"

14 / 14 papers shown
Title
Gaussian Process Upper Confidence Bounds in Distributed Point Target
  Tracking over Wireless Sensor Networks
Gaussian Process Upper Confidence Bounds in Distributed Point Target Tracking over Wireless Sensor Networks
Xingchi Liu
Lyudmila Mihaylova
Jemin George
T. Pham
69
9
0
11 Sep 2024
Privacy-aware Gaussian Process Regression
Privacy-aware Gaussian Process Regression
Rui Tuo
R. Bhattacharya
56
1
0
25 May 2023
Recurrent Neural Networks and Universal Approximation of Bayesian
  Filters
Recurrent Neural Networks and Universal Approximation of Bayesian Filters
A. Bishop
Edwin V. Bonilla
BDL
73
3
0
01 Nov 2022
Spatio-Temporal Variational Gaussian Processes
Spatio-Temporal Variational Gaussian Processes
Oliver Hamelijnck
William J. Wilkinson
Niki A. Loppi
Arno Solin
Theodoros Damoulas
AI4TS
75
35
0
02 Nov 2021
Bayes-Newton Methods for Approximate Bayesian Inference with PSD
  Guarantees
Bayes-Newton Methods for Approximate Bayesian Inference with PSD Guarantees
William J. Wilkinson
Simo Särkkä
Arno Solin
BDL
92
16
0
02 Nov 2021
Sparse Algorithms for Markovian Gaussian Processes
Sparse Algorithms for Markovian Gaussian Processes
William J. Wilkinson
Arno Solin
Vincent Adam
62
12
0
19 Mar 2021
State Space Expectation Propagation: Efficient Inference Schemes for
  Temporal Gaussian Processes
State Space Expectation Propagation: Efficient Inference Schemes for Temporal Gaussian Processes
William J. Wilkinson
Paul E. Chang
Michael Riis Andersen
Arno Solin
58
13
0
12 Jul 2020
Fast Variational Learning in State-Space Gaussian Process Models
Fast Variational Learning in State-Space Gaussian Process Models
Paul E. Chang
William J. Wilkinson
Mohammad Emtiyaz Khan
Arno Solin
BDL
79
24
0
09 Jul 2020
Linear-time inference for Gaussian Processes on one dimension
Linear-time inference for Gaussian Processes on one dimension
Jackson Loper
David M. Blei
John P. Cunningham
Liam Paninski
87
17
0
11 Mar 2020
Learning Probabilistic Intersection Traffic Models for Trajectory
  Prediction
Learning Probabilistic Intersection Traffic Models for Trajectory Prediction
Andrew Patterson
Aditya Gahlawat
N. Hovakimyan
21
2
0
05 Feb 2020
Doubly Sparse Variational Gaussian Processes
Doubly Sparse Variational Gaussian Processes
Vincent Adam
Stefanos Eleftheriadis
N. Durrande
A. Artemev
J. Hensman
85
26
0
15 Jan 2020
Black-Box Inference for Non-Linear Latent Force Models
Black-Box Inference for Non-Linear Latent Force Models
W. Ward
Tom Ryder
D. Prangle
Mauricio A. Alvarez
DRL
69
14
0
21 Jun 2019
Vecchia-Laplace approximations of generalized Gaussian processes for big
  non-Gaussian spatial data
Vecchia-Laplace approximations of generalized Gaussian processes for big non-Gaussian spatial data
Daniel Zilber
Matthias Katzfuss
84
34
0
18 Jun 2019
Recurrent Neural Filters: Learning Independent Bayesian Filtering Steps
  for Time Series Prediction
Recurrent Neural Filters: Learning Independent Bayesian Filtering Steps for Time Series Prediction
Bryan Lim
S. Zohren
Stephen J. Roberts
BDLAI4TS
61
40
0
23 Jan 2019
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