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Efficient Learning of the Parameters of Non-Linear Models using Differentiable Resampling in Particle Filters

2 November 2021

Papers citing "Efficient Learning of the Parameters of Non-Linear Models using Differentiable Resampling in Particle Filters"

27 / 27 papers shown

Title
Differentiable Particle Filters through Conditional Normalizing Flow Xiongjie Chen Hao Wen Yunpeng Li 40 21 0 01 Jul 2021
Differentiable Particle Filtering without Modifying the Forward Pass Adam Scibior Frank Wood 60 19 0 18 Jun 2021
Differentiable Particle Filtering via Entropy-Regularized Optimal Transport Adrien Corenflos James Thornton George Deligiannidis Arnaud Doucet OT 69 68 0 15 Feb 2021
How to Train Your Differentiable Filter Alina Kloss Georg Martius Jeannette Bohg 105 47 0 28 Dec 2020
End-To-End Semi-supervised Learning for Differentiable Particle Filters Hao Wen Xiongjie Chen Georgios Papagiannis Conghui Hu Yunpeng Li 49 17 0 11 Nov 2020
Towards Differentiable Resampling Michael Zhu Kevin Patrick Murphy Rico Jonschkowski 51 27 0 24 Apr 2020
Model error covariance estimation in particle and ensemble Kalman filters using an online expectation-maximization algorithm T. Cocucci M. Pulido M. Lucini P. Tandeo 61 11 0 04 Mar 2020
PyTorch: An Imperative Style, High-Performance Deep Learning Library Adam Paszke Sam Gross Francisco Massa Adam Lerer James Bradbury ... Sasank Chilamkurthy Benoit Steiner Lu Fang Junjie Bai Soumith Chintala ODL 538 42,591 0 03 Dec 2019
Stochastic quasi-Newton with line-search regularization A. Wills Thomas B. Schon ODL 58 21 0 03 Sep 2019
Particle Filter Recurrent Neural Networks Xiao Ma Peter Karkus David Hsu Wee Sun Lee 58 83 0 30 May 2019
Differentiable Particle Filters: End-to-End Learning with Algorithmic Priors Rico Jonschkowski Divyam Rastogi Oliver Brock 53 135 0 28 May 2018
Particle Filter Networks with Application to Visual Localization Peter Karkus David Hsu Wee Sun Lee 3DPC 43 117 0 23 May 2018
Geometric integrators and the Hamiltonian Monte Carlo method Nawaf Bou-Rabee J. Sanz-Serna 58 98 0 14 Nov 2017
Nudging the particle filter Ömer Deniz Akyıldız Joaquín Míguez 73 27 0 25 Aug 2017
Categorical Reparameterization with Gumbel-Softmax Eric Jang S. Gu Ben Poole BDL 349 5,379 0 03 Nov 2016
Identifying the Optimal Integration Time in Hamiltonian Monte Carlo M. Betancourt 44 37 0 02 Jan 2016
Getting Started with Particle Metropolis-Hastings for Inference in Nonlinear Dynamical Models J. Dahlin Thomas B. Schon 52 25 0 05 Nov 2015
The Metropolis-Hastings algorithm Christian P. Robert 45 169 0 08 Apr 2015
Particle Metropolis adjusted Langevin algorithms for state space models Christopher Nemeth Paul Fearnhead 71 19 0 04 Feb 2014
Auto-Encoding Variational Bayes Diederik P. Kingma Max Welling BDL 455 16,923 0 20 Dec 2013
Particle Metropolis-Hastings using gradient and Hessian information J. Dahlin Fredrik Lindsten Thomas B. Schon 88 47 0 04 Nov 2013
Nested particle filters for online parameter estimation in discrete-time state-space Markov models Dan Crisan Joaquín Míguez 72 95 0 08 Aug 2013
Particle approximations of the score and observed information matrix for parameter estimation in state space models with linear computational cost Christopher Nemeth Paul Fearnhead Lyudmila Mihaylova 102 45 0 04 Jun 2013
MCMC using Hamiltonian dynamics Radford M. Neal 292 3,282 0 09 Jun 2012
The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo Matthew D. Hoffman Andrew Gelman 169 4,309 0 18 Nov 2011
Uniform Stability of a Particle Approximation of the Optimal Filter Derivative P. Del Moral Arnaud Doucet Sumeetpal S. Singh 119 29 0 13 Jun 2011
SMC^2: an efficient algorithm for sequential analysis of state-space models Nicolas Chopin Pierre E. Jacob O. Papaspiliopoulos 93 357 0 07 Jan 2011