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Probabilistic Recurrent State-Space Models

Probabilistic Recurrent State-Space Models

31 January 2018
Andreas Doerr
Christian Daniel
Martin Schiegg
D. Nguyen-Tuong
S. Schaal
Marc Toussaint
Sebastian Trimpe
ArXivPDFHTML

Papers citing "Probabilistic Recurrent State-Space Models"

27 / 27 papers shown
Title
Efficient Transformed Gaussian Process State-Space Models for Non-Stationary High-Dimensional Dynamical Systems
Efficient Transformed Gaussian Process State-Space Models for Non-Stationary High-Dimensional Dynamical Systems
Zhidi Lin
Ying Li
Feng Yin
Juan Maroñas
Alexandre Thiéry
54
0
0
24 Mar 2025
Web Agents with World Models: Learning and Leveraging Environment Dynamics in Web Navigation
Web Agents with World Models: Learning and Leveraging Environment Dynamics in Web Navigation
Hyungjoo Chae
Namyoung Kim
Kai Tzu-iunn Ong
Minju Gwak
Gwanwoo Song
Jihoon Kim
S. Kim
Dongha Lee
Jinyoung Yeo
LLMAG
33
15
0
17 Oct 2024
Amortized Control of Continuous State Space Feynman-Kac Model for Irregular Time Series
Amortized Control of Continuous State Space Feynman-Kac Model for Irregular Time Series
Byoungwoo Park
Hyungi Lee
Juho Lee
AI4TS
46
0
0
08 Oct 2024
Exact Inference for Continuous-Time Gaussian Process Dynamics
Exact Inference for Continuous-Time Gaussian Process Dynamics
K. Ensinger
Nicholas Tagliapietra
Sebastian Ziesche
Sebastian Trimpe
29
1
0
05 Sep 2023
Combining Slow and Fast: Complementary Filtering for Dynamics Learning
Combining Slow and Fast: Complementary Filtering for Dynamics Learning
K. Ensinger
Sebastian Ziesche
Barbara Rakitsch
Michael Tiemann
Sebastian Trimpe
19
2
0
27 Feb 2023
Free-Form Variational Inference for Gaussian Process State-Space Models
Free-Form Variational Inference for Gaussian Process State-Space Models
Xuhui Fan
Edwin V. Bonilla
T. O’Kane
Scott A. Sisson
16
9
0
20 Feb 2023
Sequential Estimation of Gaussian Process-based Deep State-Space Models
Sequential Estimation of Gaussian Process-based Deep State-Space Models
Yuhao Liu
Marzieh Ajirak
P. Djuric
26
12
0
29 Jan 2023
Towards Flexibility and Interpretability of Gaussian Process State-Space
  Model
Towards Flexibility and Interpretability of Gaussian Process State-Space Model
Zhidi Lin
Feng Yin
Juan Maroñas
34
7
0
21 Jan 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
29
3
0
01 Nov 2022
On Uncertainty in Deep State Space Models for Model-Based Reinforcement
  Learning
On Uncertainty in Deep State Space Models for Model-Based Reinforcement Learning
P. Becker
Gerhard Neumann
30
9
0
17 Oct 2022
A Comprehensive Review of Digital Twin -- Part 1: Modeling and Twinning
  Enabling Technologies
A Comprehensive Review of Digital Twin -- Part 1: Modeling and Twinning Enabling Technologies
Adam Thelen
Xiaoge Zhang
Olga Fink
Yan Lu
Sayan Ghosh
B. Youn
Michael D. Todd
S. Mahadevan
Chao Hu
Zhen Hu
SyDa
AI4CE
27
189
0
26 Aug 2022
Flow-based Recurrent Belief State Learning for POMDPs
Flow-based Recurrent Belief State Learning for POMDPs
Xiaoyu Chen
Yao Mu
Ping Luo
Sheng Li
Jianyu Chen
45
18
0
23 May 2022
Continual Learning of Multi-modal Dynamics with External Memory
Continual Learning of Multi-modal Dynamics with External Memory
Abdullah Akgul
Gözde B. Ünal
M. Kandemir
CLL
19
0
0
02 Mar 2022
Likelihood-Free Inference in State-Space Models with Unknown Dynamics
Likelihood-Free Inference in State-Space Models with Unknown Dynamics
Alexander Aushev
Thong Tran
Henri Pesonen
Andrew Howes
Samuel Kaski
28
1
0
02 Nov 2021
A Temporal Variational Model for Story Generation
A Temporal Variational Model for Story Generation
David Wilmot
Frank Keller
DRL
35
8
0
14 Sep 2021
Variational multiple shooting for Bayesian ODEs with Gaussian processes
Variational multiple shooting for Bayesian ODEs with Gaussian processes
Pashupati Hegde
Çağatay Yıldız
Harri Lähdesmäki
Samuel Kaski
Markus Heinonen
30
16
0
21 Jun 2021
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
Uncertainty Estimation and Calibration with Finite-State Probabilistic
  RNNs
Uncertainty Estimation and Calibration with Finite-State Probabilistic RNNs
Cheng Wang
Carolin (Haas) Lawrence
Mathias Niepert
UQCV
29
10
0
24 Nov 2020
Variational Dynamic Mixtures
Variational Dynamic Mixtures
Chen Qiu
Stephan Mandt
Maja R. Rudolph
BDL
AI4TS
16
2
0
20 Oct 2020
Mastering Atari with Discrete World Models
Mastering Atari with Discrete World Models
Danijar Hafner
Timothy Lillicrap
Mohammad Norouzi
Jimmy Ba
DRL
48
819
0
05 Oct 2020
Efficient Model-Based Reinforcement Learning through Optimistic Policy
  Search and Planning
Efficient Model-Based Reinforcement Learning through Optimistic Policy Search and Planning
Sebastian Curi
Felix Berkenkamp
Andreas Krause
33
82
0
15 Jun 2020
Learning Constrained Dynamics with Gauss Principle adhering Gaussian
  Processes
Learning Constrained Dynamics with Gauss Principle adhering Gaussian Processes
A. R. Geist
Sebastian Trimpe
25
21
0
23 Apr 2020
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
Stochastic Latent Actor-Critic: Deep Reinforcement Learning with a
  Latent Variable Model
Stochastic Latent Actor-Critic: Deep Reinforcement Learning with a Latent Variable Model
Alex X. Lee
Anusha Nagabandi
Pieter Abbeel
Sergey Levine
OffRL
BDL
33
372
0
01 Jul 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
44
30
0
13 Jun 2019
Recurrent Kalman Networks: Factorized Inference in High-Dimensional Deep
  Feature Spaces
Recurrent Kalman Networks: Factorized Inference in High-Dimensional Deep Feature Spaces
P. Becker
Harit Pandya
Gregor H. W. Gebhardt
Cheng Zhao
James Taylor
Gerhard Neumann
BDL
15
94
0
17 May 2019
Learning Nonlinear State Space Models with Hamiltonian Sequential Monte
  Carlo Sampler
Learning Nonlinear State Space Models with Hamiltonian Sequential Monte Carlo Sampler
Duo Xu
26
2
0
03 Jan 2019
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