Differentiable Particle Filtering via Entropy-Regularized Optimal Transport

15 February 2021

Adrien Corenflos

James Thornton

George Deligiannidis

Arnaud Doucet

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Papers citing "Differentiable Particle Filtering via Entropy-Regularized Optimal Transport"

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Title
DnD Filter: Differentiable State Estimation for Dynamic Systems using Diffusion Models Ziyu Wan Lin Zhao DiffM 63 0 0 03 Mar 2025
Learning to be Smooth: An End-to-End Differentiable Particle Smoother Ali Younis Erik B. Sudderth AI4TS 33 0 0 14 Feb 2025
GraphGrad: Efficient Estimation of Sparse Polynomial Representations for General State-Space Models Benjamin Cox Émilie Chouzenoux Victor Elvira 64 0 0 23 Nov 2024
Learning state and proposal dynamics in state-space models using differentiable particle filters and neural networks Benjamin Cox Santiago Segarra Victor Elvira 61 0 0 23 Nov 2024
Permutation Invariant Learning with High-Dimensional Particle Filters Akhilan Boopathy Aneesh Muppidi Peggy Yang Abhiram Iyer William Yue Ila R Fiete SSL 36 0 0 30 Oct 2024
Enhanced SMC $^2$ : Leveraging Gradient Information from Differentiable Particle Filters Within Langevin Proposals Conor Rosato Joshua Murphy Alessandro Varsi P. Horridge Simon Maskell 21 4 0 24 Jul 2024
Differentiable Cost-Parameterized Monge Map Estimators Samuel Howard George Deligiannidis Patrick Rebeschini James Thornton OT 31 1 0 12 Jun 2024
Regime Learning for Differentiable Particle Filters John-Joseph Brady Yuhui Luo Wenwu Wang Victor Elvira Yunpeng Li 16 0 0 08 May 2024
Revisiting semi-supervised training objectives for differentiable particle filters Jiaxi Li John-Joseph Brady Xiongjie Chen Yunpeng Li 22 1 0 02 May 2024
Resampling-free Particle Filters in High-dimensions Akhilan Boopathy Aneesh Muppidi Peggy Yang Abhiram Iyer William Yue Ila Fiete 23 2 0 21 Apr 2024
Differentiable and Stable Long-Range Tracking of Multiple Posterior Modes Ali Younis Erik B. Sudderth 26 4 0 12 Apr 2024
Optimal State Estimation in the Presence of Non-Gaussian Uncertainty via Wasserstein Distance Minimization Himanshu Prabhat Raktim Bhattacharya 15 1 0 06 Mar 2024
Differentiable Particle Filtering using Optimal Placement Resampling Domonkos Csuzdi Olivér Törő Tamás Bécsi 19 0 0 26 Feb 2024
Risk-Sensitive Stochastic Optimal Control as Rao-Blackwellized Markovian Score Climbing Hany Abdulsamad Sahel Iqbal Adrien Corenflos Simo Särkkä 33 2 0 21 Dec 2023
Learning Differentiable Particle Filter on the Fly Jiaxi Li Xiongjie Chen Yunpeng Li 13 1 0 10 Dec 2023
On Feynman--Kac training of partial Bayesian neural networks Zheng Zhao Sebastian Mair Thomas B. Schon Jens Sjölund 17 0 0 30 Oct 2023
Enhancing State Estimation in Robots: A Data-Driven Approach with Differentiable Ensemble Kalman Filters Xinyu Liu Geoffrey Clark Joseph Campbell Yifan Zhou H. B. Amor 21 10 0 19 Aug 2023
Extending Path-Dependent NJ-ODEs to Noisy Observations and a Dependent Observation Framework William Andersson Jakob Heiss Florian Krach Josef Teichmann 17 2 0 24 Jul 2023
Sparse Graphical Linear Dynamical Systems Émilie Chouzenoux Victor Elvira 17 7 0 06 Jul 2023
Resampling Gradients Vanish in Differentiable Sequential Monte Carlo Samplers Johannes Zenn Robert Bamler 27 3 0 27 Apr 2023
Stochastic filtering with moment representation Zheng Zhao Juha Sarmavuori 14 0 0 24 Mar 2023
Differentiable Bootstrap Particle Filters for Regime-Switching Models Wenhan Li Xiongjie Chen Wenwu Wang Victor Elvira Yunpeng Li 19 6 0 20 Feb 2023
An overview of differentiable particle filters for data-adaptive sequential Bayesian inference Xiongjie Chen Yunpeng Li 12 14 0 19 Feb 2023
Unsupervised Learning of Sampling Distributions for Particle Filters Fernando Gama Nicolas Zilberstein Martín Sevilla Richard Baraniuk Santiago Segarra 30 9 0 02 Feb 2023
Transport with Support: Data-Conditional Diffusion Bridges Ella Tamir Martin Trapp Arno Solin DiffM OT 23 7 0 31 Jan 2023
Reduced-Order Autodifferentiable Ensemble Kalman Filters Yuming Chen D. Sanz-Alonso Rebecca Willett 26 8 0 27 Jan 2023
Sequential Bayesian Learning for Hidden Semi-Markov Models Patrick Aschermayr K. Kalogeropoulos 11 0 0 25 Jan 2023
Particle-Based Score Estimation for State Space Model Learning in Autonomous Driving Angad Singh Omar Makhlouf Maximilian Igl Joao Messias Arnaud Doucet Shimon Whiteson 31 2 0 14 Dec 2022
Automatic Differentiation of Programs with Discrete Randomness Gaurav Arya Moritz Schauer Frank Schafer Chris Rackauckas 16 33 0 16 Oct 2022
Rethinking Initialization of the Sinkhorn Algorithm James Thornton Marco Cuturi OT 13 10 0 15 Jun 2022
Conditional Measurement Density Estimation in Sequential Monte Carlo via Normalizing Flow Xiongjie Chen Yunpeng Li 13 6 0 16 Mar 2022
De-Sequentialized Monte Carlo: a parallel-in-time particle smoother Adrien Corenflos Nicolas Chopin Simo Särkkä 11 7 0 04 Feb 2022
Continual Repeated Annealed Flow Transport Monte Carlo A. G. Matthews Michael Arbel Danilo Jimenez Rezende Arnaud Doucet OT 17 46 0 31 Jan 2022
The Coupled Rejection Sampler Adrien Corenflos Simo Särkkä 17 4 0 24 Jan 2022
Compositional Learning-based Planning for Vision POMDPs Sampada Deglurkar M. H. Lim Johnathan Tucker Zachary Sunberg Aleksandra Faust Claire Tomlin 25 4 0 17 Dec 2021
Efficient Learning of the Parameters of Non-Linear Models using Differentiable Resampling in Particle Filters Conor Rosato Vincent Beraud P. Horridge Thomas B. Schon Simon Maskell 8 14 0 02 Nov 2021
Online Variational Filtering and Parameter Learning Andrew Campbell Yuyang Shi Tom Rainforth Arnaud Doucet BDL 20 21 0 26 Oct 2021
Variational Marginal Particle Filters Jinlin Lai Justin Domke Daniel Sheldon 21 9 0 30 Sep 2021
Quantitative Uniform Stability of the Iterative Proportional Fitting Procedure George Deligiannidis Valentin De Bortoli Arnaud Doucet 11 24 0 18 Aug 2021
Auto-differentiable Ensemble Kalman Filters Yuming Chen D. Sanz-Alonso Rebecca Willett 29 33 0 16 Jul 2021
Differentiable Particle Filters through Conditional Normalizing Flow Xiongjie Chen Hao Wen Yunpeng Li 13 20 0 01 Jul 2021
Differentiable Particle Filtering without Modifying the Forward Pass Adam Scibior Frank D. Wood 10 19 0 18 Jun 2021
Differentiable SLAM-net: Learning Particle SLAM for Visual Navigation Peter Karkus Shaojun Cai David Hsu 9 65 0 17 May 2021
How to Train Your Differentiable Filter Alina Kloss Georg Martius Jeannette Bohg 26 46 0 28 Dec 2020
An invitation to sequential Monte Carlo samplers Chenguang Dai J. Heng Pierre E. Jacob N. Whiteley 50 65 0 23 Jul 2020
Stochastic Backpropagation through Mixture Density Distributions Alex Graves BDL 41 45 0 19 Jul 2016