Variational Gaussian Process State-Space Models

18 June 2014

Papers citing "Variational Gaussian Process State-Space Models"

32 / 32 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
Data-Efficient Kernel Methods for Learning Differential Equations and Their Solution Operators: Algorithms and Error Analysis Yasamin Jalalian Juan Felipe Osorio Ramirez Alexander W. Hsu Bamdad Hosseini H. Owhadi 46 0 0 02 Mar 2025
Modeling Latent Neural Dynamics with Gaussian Process Switching Linear Dynamical Systems Amber Hu D. Zoltowski Aditya Nair David Anderson Lea Duncker Scott W. Linderman 36 3 0 19 Jul 2024
Future Aware Safe Active Learning of Time Varying Systems using Gaussian Processes Markus Lange-Hegermann Christoph Zimmer AI4TS 47 0 0 17 May 2024
A projected nonlinear state-space model for forecasting time series signals Christian Donner Anuj Mishra Hideaki Shimazaki AI4TS 21 0 0 22 Nov 2023
Multi-Response Heteroscedastic Gaussian Process Models and Their Inference Taehee Lee Jun S. Liu 13 1 0 29 Aug 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
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 Zhidi Lin Feng Yin Juan Maroñas 34 7 0 21 Jan 2023
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
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
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
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 41 2 0 03 Jun 2021
Variational Filtering with Copula Models for SLAM John D. Martin Kevin Doherty Caralyn Cyr Brendan Englot J. Leonard 19 3 0 02 Aug 2020
Sparse Gaussian Processes with Spherical Harmonic Features Vincent Dutordoir N. Durrande J. Hensman 27 54 0 30 Jun 2020
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 Qi She Anqi Wu BDL 18 34 0 01 Jul 2019
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 Yuan Zhao Josue Nassar I. Jordan M. Bugallo Il Memming Park BDL 34 21 0 04 Jun 2019
Learning Nonlinear State Space Models with Hamiltonian Sequential Monte Carlo Sampler Duo Xu 18 2 0 03 Jan 2019
Learning dynamical systems with particle stochastic approximation EM Andreas Svensson Fredrik Lindsten 29 9 0 25 Jun 2018
Identification of Gaussian Process State Space Models Stefanos Eleftheriadis Tom Nicholson M. Deisenroth J. Hensman 24 111 0 30 May 2017
Learning Scalable Deep Kernels with Recurrent Structure Maruan Al-Shedivat A. Wilson Yunus Saatchi Zhiting Hu Eric P. Xing BDL 13 104 0 27 Oct 2016
Linear dynamical neural population models through nonlinear embeddings Yuanjun Gao Evan Archer Liam Paninski John P. Cunningham 11 155 0 26 May 2016
A Unifying Framework for Gaussian Process Pseudo-Point Approximations using Power Expectation Propagation T. Bui Josiah Yan Richard Turner 21 25 0 23 May 2016
Variational Latent Gaussian Process for Recovering Single-Trial Dynamics from Population Spike Trains Yuan Zhao Il-Su Park 13 116 0 11 Apr 2016
A flexible state space model for learning nonlinear dynamical systems Andreas Svensson Thomas B. Schon 14 104 0 17 Mar 2016
System Identification through Online Sparse Gaussian Process Regression with Input Noise Hildo Bijl Thomas B. Schon J. Wingerden M. Verhaegen 39 41 0 29 Jan 2016
Recurrent Gaussian Processes C. L. C. Mattos Zhenwen Dai Andreas C. Damianou Jeremy Forth G. Barreto Neil D. Lawrence BDL 18 75 0 20 Nov 2015
Neural Adaptive Sequential Monte Carlo S. Gu Zoubin Ghahramani Richard Turner BDL 16 145 0 10 Jun 2015
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