Overcoming Mean-Field Approximations in Recurrent Gaussian Process Models

13 June 2019

Alessandro Davide Ialongo

Papers citing "Overcoming Mean-Field Approximations in Recurrent Gaussian Process Models"

23 / 23 papers shown

Title
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
Recursive Gaussian Process State Space Model Tengjie Zheng Lin Cheng Shengping Gong Xu Huang 74 0 0 22 Nov 2024
Ensemble Kalman Filtering Meets Gaussian Process SSM for Non-Mean-Field and Online Inference Zhidi Lin Yiyong Sun Feng Yin Alexandre Thiéry 29 4 0 10 Dec 2023
Sampling-Free Probabilistic Deep State-Space Models Andreas Look M. Kandemir Barbara Rakitsch Jan Peters 16 2 0 15 Sep 2023
Out of Distribution Detection via Domain-Informed Gaussian Process State Space Models Alonso Marco Elias Morley Claire Tomlin 34 2 0 13 Sep 2023
Towards Efficient Modeling and Inference in Multi-Dimensional Gaussian Process State-Space Models Zhidi Lin Juan Maroñas Ying Li Feng Yin Sergios Theodoridis 24 3 0 03 Sep 2023
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
Towards Flexibility and Interpretability of Gaussian Process State-Space Model Zhidi Lin Feng Yin Juan Maroñas 34 7 0 21 Jan 2023
Towards AI-controlled FES-restoration of arm movements: Controlling for progressive muscular fatigue with Gaussian state-space models Nat Wannawas Aldo A. Faisal 11 5 0 10 Jan 2023
Output-Dependent Gaussian Process State-Space Model Zhidi Lin Lei Cheng Feng Yin Le Xu Shuguang Cui UQCV 41 5 0 15 Dec 2022
The Past Does Matter: Correlation of Subsequent States in Trajectory Predictions of Gaussian Process Models Steffen Ridderbusch Sina Ober-Blobaum Paul Goulart 24 2 0 20 Nov 2022
Recurrent Neural Networks and Universal Approximation of Bayesian Filters A. Bishop Edwin V. Bonilla BDL 29 3 0 01 Nov 2022
Continual Learning of Multi-modal Dynamics with External Memory Abdullah Akgul Gözde B. Ünal M. Kandemir CLL 19 0 0 02 Mar 2022
Traversing Time with Multi-Resolution Gaussian Process State-Space Models Krista Longi J. Lindinger Olaf Duennbier M. Kandemir Arto Klami Barbara Rakitsch 16 3 0 06 Dec 2021
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
Inferring the Structure of Ordinary Differential Equations Juliane Weilbach S. Gerwinn Christian D. Weilbach M. Kandemir 32 3 0 05 Jul 2021
Variational multiple shooting for Bayesian ODEs with Gaussian processes Pashupati Hegde Çağatay Yıldız Harri Lähdesmäki Samuel Kaski Markus Heinonen 27 16 0 21 Jun 2021
Deep Probabilistic Time Series Forecasting using Augmented Recurrent Input for Dynamic Systems Haitao Liu Changjun Liu Xiaomo Jiang Xudong Chen Shuhua Yang Xiaofang Wang BDL AI4TS 27 2 0 03 Jun 2021
Structure-preserving Gaussian Process Dynamics K. Ensinger Friedrich Solowjow Sebastian Ziesche Michael Tiemann Sebastian Trimpe 37 9 0 02 Feb 2021
Pathwise Conditioning of Gaussian Processes James T. Wilson Viacheslav Borovitskiy Alexander Terenin P. Mostowsky M. Deisenroth 18 57 0 08 Nov 2020
Stochastic embeddings of dynamical phenomena through variational autoencoders C. A. García P. Félix J. Presedo A. Otero BDL 19 2 0 13 Oct 2020
On Simulation and Trajectory Prediction with Gaussian Process Dynamics Lukas Hewing Elena Arcari Lukas P. Frohlich M. Zeilinger 17 35 0 23 Dec 2019
Structured Variational Inference in Unstable Gaussian Process State Space Models Silvan Melchior Sebastian Curi Felix Berkenkamp Andreas Krause 17 4 0 16 Jul 2019