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Variational Gaussian Process State-Space Models

18 June 2014

Papers citing "Variational Gaussian Process State-Space Models"

37 / 87 papers shown

Title
Neural Dynamics Discovery via Gaussian Process Recurrent Neural Networks Qi She Anqi Wu BDL 53 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 79 30 0 13 Jun 2019
$A General $\mathcal{O}(n^2)$ Hyper-Parameter Optimization for Gaussian Process Regression with Cross-Validation and Non-linearly Constrained ADMM$ A General $\mathcal{O}(n^2)$ Hyper-Parameter Optimization for Gaussian Process Regression with Cross-Validation and Non-linearly Constrained ADMM Linning Xu Feng Yin Jiawei Zhang Zhi-Quan Luo Shuguang Cui GP 62 0 0 06 Jun 2019
Physics Enhanced Data-Driven Models with Variational Gaussian Processes Daniel L. Marino Milos Manic 23 3 0 05 Jun 2019
Streaming Variational Monte Carlo Yuan Zhao Josue Nassar I. Jordan M. Bugallo Il Memming Park BDL 280 21 0 04 Jun 2019
Learning interpretable continuous-time models of latent stochastic dynamical systems Lea Duncker G. Bohner Julien Boussard M. Sahani 62 77 0 12 Feb 2019
Modeling neural dynamics during speech production using a state space variational autoencoder Pengfei Sun David A. Moses E. Chang BDL 13 3 0 13 Jan 2019
Learning Nonlinear State Space Models with Hamiltonian Sequential Monte Carlo Sampler Duo Xu 64 2 0 03 Jan 2019
Evaluating the squared-exponential covariance function in Gaussian processes with integral observations J. Hendriks Carl Jidling A. Wills Thomas B. Schon 63 9 0 18 Dec 2018
Non-Factorised Variational Inference in Dynamical Systems Alessandro Davide Ialongo Mark van der Wilk J. Hensman C. Rasmussen 74 6 0 14 Dec 2018
Closed-form Inference and Prediction in Gaussian Process State-Space Models Alessandro Davide Ialongo Mark van der Wilk C. Rasmussen 77 8 0 10 Dec 2018
Tree-Structured Recurrent Switching Linear Dynamical Systems for Multi-Scale Modeling Josue Nassar Scott W. Linderman M. Bugallo Il-Su Park AI4CE 114 73 0 29 Nov 2018
Mean Square Prediction Error of Misspecified Gaussian Process Models Thomas Beckers Jonas Umlauft Sandra Hirche 60 19 0 16 Nov 2018
InfoSSM: Interpretable Unsupervised Learning of Nonparametric State-Space Model for Multi-modal Dynamics Young-Jin Park Han-Lim Choi 16 0 0 19 Sep 2018
When Gaussian Process Meets Big Data: A Review of Scalable GPs Haitao Liu Yew-Soon Ong Xiaobo Shen Jianfei Cai GP 133 697 0 03 Jul 2018
A Data-Driven Approach to Dynamically Adjust Resource Allocation for Compute Clusters Francesco Pace Dimitrios Milios D. Carra D. Venzano Pietro Michiardi 43 4 0 01 Jul 2018
Learning dynamical systems with particle stochastic approximation EM Andreas Svensson Fredrik Lindsten 100 9 0 25 Jun 2018
Learning unknown ODE models with Gaussian processes Markus Heinonen Çağatay Yıldız Henrik Mannerstrom Jukka Intosalmi Harri Lähdesmäki 55 94 0 12 Mar 2018
Specialized Interior Point Algorithm for Stable Nonlinear System Identification Jack Umenberger I. Manchester 46 33 0 02 Mar 2018
Conditionally Independent Multiresolution Gaussian Processes Jalil Taghia Thomas B. Schon 64 1 0 25 Feb 2018
State Space Gaussian Processes with Non-Gaussian Likelihood H. Nickisch Arno Solin A. Grigorevskiy GP 74 32 0 13 Feb 2018
Probabilistic Recurrent State-Space Models Andreas Doerr Christian Daniel Martin Schiegg D. Nguyen-Tuong S. Schaal Marc Toussaint Sebastian Trimpe 89 123 0 31 Jan 2018
Deep Recurrent Gaussian Process with Variational Sparse Spectrum Approximation Roman Föll B. Haasdonk Markus Hanselmann Holger Ulmer BDL 60 6 0 02 Nov 2017
Variational online learning of neural dynamics Yuan Zhao Il Memming Park BDL OffRL 79 9 0 27 Jul 2017
Identification of Gaussian Process State Space Models Stefanos Eleftheriadis Tom Nicholson M. Deisenroth J. Hensman 90 113 0 30 May 2017
A Mutually-Dependent Hadamard Kernel for Modelling Latent Variable Couplings Sami Remes Markus Heinonen Samuel Kaski 91 3 0 27 Feb 2017
Recurrent Image Captioner: Describing Images with Spatial-Invariant Transformation and Attention Filtering Hao Liu Yang Yang Fumin Shen Lixin Duan Heng Tao Shen 65 9 0 15 Dec 2016
Learning Scalable Deep Kernels with Recurrent Structure Maruan Al-Shedivat A. Wilson Yunus Saatchi Zhiting Hu Eric Xing BDL 100 105 0 27 Oct 2016
Incremental Nonlinear System Identification and Adaptive Particle Filtering Using Gaussian Process Vahid Bastani L. Marcenaro C. Regazzoni 15 0 0 30 Aug 2016
Linear dynamical neural population models through nonlinear embeddings Yuanjun Gao Evan Archer Liam Paninski John P. Cunningham 84 155 0 26 May 2016
A Unifying Framework for Gaussian Process Pseudo-Point Approximations using Power Expectation Propagation T. Bui Josiah Yan Richard Turner 89 25 0 23 May 2016
Variational Latent Gaussian Process for Recovering Single-Trial Dynamics from Population Spike Trains Yuan Zhao Il-Su Park 105 117 0 11 Apr 2016
A flexible state space model for learning nonlinear dynamical systems Andreas Svensson Thomas B. Schon 82 104 0 17 Mar 2016
System Identification through Online Sparse Gaussian Process Regression with Input Noise Hildo Bijl Thomas B. Schon J. Wingerden M. Verhaegen 129 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 96 75 0 20 Nov 2015
Neural Adaptive Sequential Monte Carlo S. Gu Zoubin Ghahramani Richard Turner BDL 92 147 0 10 Jun 2015
Computationally Efficient Bayesian Learning of Gaussian Process State Space Models Andreas Svensson Arno Solin Simo Särkkä Thomas B. Schon 81 57 0 07 Jun 2015