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Recurrent Gaussian Processes

Recurrent Gaussian Processes

20 November 2015
C. L. C. Mattos
Zhenwen Dai
Andreas C. Damianou
Jeremy Forth
G. Barreto
Neil D. Lawrence
    BDL
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Papers citing "Recurrent Gaussian Processes"

18 / 18 papers shown
Title
Residual Deep Gaussian Processes on Manifolds
Residual Deep Gaussian Processes on Manifolds
Kacper Wyrwal
Andreas Krause
Viacheslav Borovitskiy
BDL
49
0
0
31 Oct 2024
Bézier Curve Gaussian Processes
Bézier Curve Gaussian Processes
Ronny Hug
S. Becker
Wolfgang Hubner
Michael Arens
Jürgen Beyerer
21
4
0
03 May 2022
RNN with Particle Flow for Probabilistic Spatio-temporal Forecasting
RNN with Particle Flow for Probabilistic Spatio-temporal Forecasting
Soumyasundar Pal
Liheng Ma
Yingxue Zhang
Mark J. Coates
BDL
AI4TS
33
22
0
10 Jun 2021
Recurrent Attentive Neural Process for Sequential Data
Recurrent Attentive Neural Process for Sequential Data
Shenghao Qin
Jiacheng Zhu
Jimmy Qin
Wenshuo Wang
Ding Zhao
BDL
AI4TS
27
38
0
17 Oct 2019
Learning GPLVM with arbitrary kernels using the unscented transformation
Learning GPLVM with arbitrary kernels using the unscented transformation
Daniel Augusto R. M. A. de Souza
Diego Mesquita
C. L. C. Mattos
Joao P. P. Gomes
29
0
0
03 Jul 2019
Neural Dynamics Discovery via Gaussian Process Recurrent Neural Networks
Neural Dynamics Discovery via Gaussian Process Recurrent Neural Networks
Qi She
Anqi Wu
BDL
18
34
0
01 Jul 2019
The Functional Neural Process
The Functional Neural Process
Christos Louizos
Xiahan Shi
Klamer Schutte
Max Welling
BDL
38
77
0
19 Jun 2019
Overcoming Mean-Field Approximations in Recurrent Gaussian Process
  Models
Overcoming Mean-Field Approximations in Recurrent Gaussian Process Models
Alessandro Davide Ialongo
Mark van der Wilk
J. Hensman
C. Rasmussen
33
30
0
13 Jun 2019
Streaming Variational Monte Carlo
Streaming Variational Monte Carlo
Yuan Zhao
Josue Nassar
I. Jordan
M. Bugallo
Il Memming Park
BDL
34
21
0
04 Jun 2019
Neural Likelihoods for Multi-Output Gaussian Processes
Neural Likelihoods for Multi-Output Gaussian Processes
M. Jankowiak
Jacob R. Gardner
UQCV
BDL
29
3
0
31 May 2019
Learning dynamical systems with particle stochastic approximation EM
Learning dynamical systems with particle stochastic approximation EM
Andreas Svensson
Fredrik Lindsten
33
9
0
25 Jun 2018
Identification of Gaussian Process State Space Models
Identification of Gaussian Process State Space Models
Stefanos Eleftheriadis
Tom Nicholson
M. Deisenroth
J. Hensman
24
111
0
30 May 2017
Doubly Stochastic Variational Inference for Deep Gaussian Processes
Doubly Stochastic Variational Inference for Deep Gaussian Processes
Hugh Salimbeni
M. Deisenroth
BDL
GP
34
415
0
24 May 2017
Learning Scalable Deep Kernels with Recurrent Structure
Learning Scalable Deep Kernels with Recurrent Structure
Maruan Al-Shedivat
A. Wilson
Yunus Saatchi
Zhiting Hu
Eric Xing
BDL
13
104
0
27 Oct 2016
How priors of initial hyperparameters affect Gaussian process regression
  models
How priors of initial hyperparameters affect Gaussian process regression models
Zexun Chen
Bo Wang
18
86
0
25 May 2016
A flexible state space model for learning nonlinear dynamical systems
A flexible state space model for learning nonlinear dynamical systems
Andreas Svensson
Thomas B. Schon
16
104
0
17 Mar 2016
Inverse Reinforcement Learning via Deep Gaussian Process
Inverse Reinforcement Learning via Deep Gaussian Process
Ming Jin
Andreas C. Damianou
Pieter Abbeel
C. Spanos
OffRL
BDL
GP
20
22
0
26 Dec 2015
Computationally Efficient Bayesian Learning of Gaussian Process State
  Space Models
Computationally Efficient Bayesian Learning of Gaussian Process State Space Models
Andreas Svensson
Arno Solin
Simo Särkkä
Thomas B. Schon
24
57
0
07 Jun 2015
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