Variational Sequential Monte Carlo

31 May 2017

Papers citing "Variational Sequential Monte Carlo"

50 / 141 papers shown

Title
Trust-Region Twisted Policy Improvement Joery A. de Vries Jinke He Yaniv Oren M. Spaan OffRL LRM 37 0 0 08 Apr 2025
End-To-End Learning of Gaussian Mixture Priors for Diffusion Sampler Denis Blessing Xiaogang Jia Gerhard Neumann DiffM 53 0 0 01 Mar 2025
Variational Pseudo Marginal Methods for Jet Reconstruction in Particle Physics Hanming Yang A. Moretti Sebastian Macaluso Philippe Chlenski C. A. Naesseth I. Pe’er BDL 47 1 0 03 Jan 2025
Learning state and proposal dynamics in state-space models using differentiable particle filters and neural networks Benjamin Cox Santiago Segarra Victor Elvira 81 0 0 23 Nov 2024
Recursive Learning of Asymptotic Variational Objectives Alessandro Mastrototaro Mathias Müller Jimmy Olsson 28 0 0 04 Nov 2024
Meta-Dynamical State Space Models for Integrative Neural Data Analysis Ayesha Vermani Josue Nassar Hyungju Jeon Matthew Dowling Il Memming Park 41 1 0 07 Oct 2024
Divide-and-Conquer Predictive Coding: a structured Bayesian inference algorithm Eli Sennesh Hao Wu Tommaso Salvatori 40 0 0 11 Aug 2024
Inferring stochastic low-rank recurrent neural networks from neural data Matthijs Pals A Erdem Sağtekin Felix Pei Manuel Gloeckler Jakob H Macke 43 7 0 24 Jun 2024
Probabilistic Programming with Programmable Variational Inference McCoy R. Becker Alexander K. Lew Xiaoyan Wang Matin Ghavami Mathieu Huot Martin Rinard Vikash K. Mansinghka 59 3 0 22 Jun 2024
KalMamba: Towards Efficient Probabilistic State Space Models for RL under Uncertainty P. Becker Niklas Freymuth Gerhard Neumann Mamba 26 2 0 21 Jun 2024
Regime Learning for Differentiable Particle Filters John-Joseph Brady Yuhui Luo Wenwu Wang Victor Elvira Yunpeng Li 33 0 0 08 May 2024
Revisiting semi-supervised training objectives for differentiable particle filters Jiaxi Li John-Joseph Brady Xiongjie Chen Yunpeng Li 28 1 0 02 May 2024
Multi-AGV Path Planning Method via Reinforcement Learning and Particle Filters Shao Shuo 34 1 0 27 Mar 2024
Sequential Monte Carlo for Inclusive KL Minimization in Amortized Variational Inference Declan McNamara J. Loper Jeffrey Regier BDL 48 2 0 15 Mar 2024
Differentiable Particle Filtering using Optimal Placement Resampling Domonkos Csuzdi Olivér Törő Tamás Bécsi 37 0 0 26 Feb 2024
Bayesian Multi-Task Transfer Learning for Soft Prompt Tuning Haeju Lee Minchan Jeong SeYoung Yun Kee-Eung Kim AAML VPVLM 53 3 0 13 Feb 2024
Provably Scalable Black-Box Variational Inference with Structured Variational Families Joohwan Ko Kyurae Kim W. Kim Jacob R. Gardner BDL 35 2 0 19 Jan 2024
Online Variational Sequential Monte Carlo Alessandro Mastrototaro Jimmy Olsson BDL OffRL 35 3 0 19 Dec 2023
Learning Differentiable Particle Filter on the Fly Jiaxi Li Xiongjie Chen Yunpeng Li 36 1 0 10 Dec 2023
On Feynman--Kac training of partial Bayesian neural networks Zheng Zhao Sebastian Mair Thomas B. Schon Jens Sjölund 40 0 0 30 Oct 2023
Using Autodiff to Estimate Posterior Moments, Marginals and Samples Sam Bowyer Thomas Heap Laurence Aitchison 43 1 0 26 Oct 2023
Variational autoencoder with weighted samples for high-dimensional non-parametric adaptive importance sampling J. Demange-Chryst François Bachoc Jérome Morio Timothé Krauth 32 2 0 13 Oct 2023
Reparameterized Variational Rejection Sampling M. Jankowiak Du Phan DRL BDL 24 1 0 26 Sep 2023
NAS-X: Neural Adaptive Smoothing via Twisting Dieterich Lawson Michael Y. Li Scott W. Linderman 20 1 0 28 Aug 2023
Ensemble Kalman Filters with Resampling Omar Al Ghattas Jiajun Bao D. Sanz-Alonso 24 6 0 17 Aug 2023
Last layer state space model for representation learning and uncertainty quantification Max H. Cohen M. Charbit Sylvain Le Corff UQCV BDL 30 1 0 04 Jul 2023
Adaptive Annealed Importance Sampling with Constant Rate Progress Shirin Goshtasbpour Victor Cohen Fernando Perez-Cruz 32 7 0 27 Jun 2023
Score-based Data Assimilation François Rozet Gilles Louppe 48 32 0 18 Jun 2023
Massively Parallel Reweighted Wake-Sleep Thomas Heap Gavin Leech Laurence Aitchison BDL 24 2 0 18 May 2023
Variational Nonlinear Kalman Filtering with Unknown Process Noise Covariance Hua Lan Jinjie Hu Zengfu Wang Q. Cheng 21 10 0 06 May 2023
Cheap and Deterministic Inference for Deep State-Space Models of Interacting Dynamical Systems Andreas Look M. Kandemir Barbara Rakitsch Jan Peters BDL 38 6 0 02 May 2023
Resampling Gradients Vanish in Differentiable Sequential Monte Carlo Samplers Johannes Zenn Robert Bamler 39 3 0 27 Apr 2023
U-Statistics for Importance-Weighted Variational Inference Javier Burroni Kenta Takatsu Justin Domke Daniel Sheldon 18 1 0 27 Feb 2023
An overview of differentiable particle filters for data-adaptive sequential Bayesian inference Xiongjie Chen Yunpeng Li 33 14 0 19 Feb 2023
Reduced-Order Autodifferentiable Ensemble Kalman Filters Yuming Chen D. Sanz-Alonso Rebecca Willett 41 8 0 27 Jan 2023
Statistical Distance Based Deterministic Offspring Selection in SMC Methods Oskar Kviman Hazal Koptagel Harald Melin J. Lagergren 22 0 0 23 Dec 2022
Particle-Based Score Estimation for State Space Model Learning in Autonomous Driving Angad Singh Omar Makhlouf Maximilian Igl Joao Messias Arnaud Doucet Shimon Whiteson 51 2 0 14 Dec 2022
Nonlinear System Identification: Learning while respecting physical models using a sequential Monte Carlo method A. Wigren Johan Wågberg Fredrik Lindsten A. Wills Thomas B. Schon 24 10 0 26 Oct 2022
Efficient variational approximations for state space models Rubén Loaiza-Maya D. Nibbering 11 1 0 20 Oct 2022
On Uncertainty in Deep State Space Models for Model-Based Reinforcement Learning P. Becker Gerhard Neumann 30 9 0 17 Oct 2022
A Variational Perspective on Generative Flow Networks Heiko Zimmermann Fredrik Lindsten Jan-Willem van de Meent C. A. Naesseth 22 32 0 14 Oct 2022
Multi-Task Dynamical Systems Alex Bird Christopher K. I. Williams Christopher Hawthorne AI4TS 16 1 0 08 Oct 2022
Optimization of Annealed Importance Sampling Hyperparameters Shirin Goshtasbpour Fernando Perez-Cruz 37 1 0 27 Sep 2022
SIXO: Smoothing Inference with Twisted Objectives Dieterich Lawson Allan Raventós Andrew Warrington Scott W. Linderman BDL 21 15 0 13 Jun 2022
Factored Conditional Filtering: Tracking States and Estimating Parameters in High-Dimensional Spaces Dawei Chen Samuel Yang-Zhao John Lloyd K. S. Ng AI4TS 4 1 0 05 Jun 2022
Recursive Monte Carlo and Variational Inference with Auxiliary Variables Alexander K. Lew Marco F. Cusumano-Towner Vikash K. Mansinghka BDL 24 10 0 05 Mar 2022
De-Sequentialized Monte Carlo: a parallel-in-time particle smoother Adrien Corenflos Nicolas Chopin Simo Särkkä 39 6 0 04 Feb 2022
Continual Repeated Annealed Flow Transport Monte Carlo A. G. Matthews Michael Arbel Danilo Jimenez Rezende Arnaud Doucet OT 42 46 0 31 Jan 2022
Uphill Roads to Variational Tightness: Monotonicity and Monte Carlo Objectives Pierre-Alexandre Mattei J. Frellsen 29 4 0 26 Jan 2022
Surrogate Likelihoods for Variational Annealed Importance Sampling M. Jankowiak Du Phan BDL 35 13 0 22 Dec 2021