Likelihood-Free Inference in State-Space Models with Unknown Dynamics

2 November 2021

Papers citing "Likelihood-Free Inference in State-Space Models with Unknown Dynamics"

31 / 31 papers shown

Title
Likelihood-Free Inference with Deep Gaussian Processes Alexander Aushev Henri Pesonen Markus Heinonen J. Corander Samuel Kaski GP 60 10 0 18 Jun 2020
Differentiable Expected Hypervolume Improvement for Parallel Multi-Objective Bayesian Optimization Sam Daulton Maximilian Balandat E. Bakshy 44 242 0 09 Jun 2020
On Contrastive Learning for Likelihood-free Inference Conor Durkan Iain Murray George Papamakarios BDL 204 123 0 10 Feb 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 493 42,407 0 03 Dec 2019
The frontier of simulation-based inference Kyle Cranmer Johann Brehmer Gilles Louppe AI4CE 172 851 0 04 Nov 2019
Structured Variational Inference in Unstable Gaussian Process State Space Models Silvan Melchior Sebastian Curi Felix Berkenkamp Andreas Krause 54 4 0 16 Jul 2019
Overcoming Mean-Field Approximations in Recurrent Gaussian Process Models Alessandro Davide Ialongo Mark van der Wilk J. Hensman C. Rasmussen 72 30 0 13 Jun 2019
Automatic Posterior Transformation for Likelihood-Free Inference David S. Greenberg M. Nonnenmacher Jakob H. Macke 368 329 0 17 May 2019
Learning to Predict the Cosmological Structure Formation Siyu He Yin Li Yu Feng S. Ho Siamak Ravanbakhsh Wei Chen Barnabás Póczós 64 170 0 15 Nov 2018
Maximizing acquisition functions for Bayesian optimization James T. Wilson Frank Hutter M. Deisenroth 119 246 0 25 May 2018
Sequential Neural Likelihood: Fast Likelihood-free Inference with Autoregressive Flows George Papamakarios D. Sterratt Iain Murray BDL 525 367 0 18 May 2018
UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction Leland McInnes John Healy James Melville 157 9,413 0 09 Feb 2018
Probabilistic Recurrent State-Space Models Andreas Doerr Christian Daniel Martin Schiegg D. Nguyen-Tuong S. Schaal Marc Toussaint Sebastian Trimpe 64 122 0 31 Jan 2018
Advances in Variational Inference Cheng Zhang Judith Butepage Hedvig Kjellström Stephan Mandt BDL 175 691 0 15 Nov 2017
Flexible statistical inference for mechanistic models of neural dynamics Jan-Matthis Lueckmann P. J. Gonçalves Giacomo Bassetto Kaan Öcal M. Nonnenmacher Jakob H. Macke 166 245 0 06 Nov 2017
ELFI: Engine for Likelihood-Free Inference Jarno Lintusaari H. Vuollekoski A. Kangasrääsiö Kusti Skytén Marko Jarvenpaa Pekka Marttinen Michael U. Gutmann Aki Vehtari J. Corander Samuel Kaski 53 73 0 02 Aug 2017
Proximal Policy Optimization Algorithms John Schulman Filip Wolski Prafulla Dhariwal Alec Radford Oleg Klimov OffRL 487 19,019 0 20 Jul 2017
OpenAI Gym Greg Brockman Vicki Cheung Ludwig Pettersson Jonas Schneider John Schulman Jie Tang Wojciech Zaremba OffRL ODL 214 5,076 0 05 Jun 2016
Deep Variational Bayes Filters: Unsupervised Learning of State Space Models from Raw Data Maximilian Karl Maximilian Sölch Justin Bayer Patrick van der Smagt BDL 49 375 0 20 May 2016
Auxiliary Likelihood-Based Approximate Bayesian Computation in State Space Models G. Martin Brendan P. M. McCabe David T. Frazier Worapree Maneesoonthorn Christian P. Robert 52 44 0 27 Apr 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.2K 193,878 0 10 Dec 2015
Bayesian Optimization for Likelihood-Free Inference of Simulator-Based Statistical Models Michael U. Gutmann J. Corander 150 286 0 14 Jan 2015
Variational Gaussian Process State-Space Models R. Frigola Yutian Chen C. Rasmussen BDL 56 178 0 18 Jun 2014
Parameter Estimation in Hidden Markov Models with Intractable Likelihoods Using Sequential Monte Carlo S. Yıldırım Sumeetpal S. Singh Thomas Dean Ajay Jasra 74 36 0 17 Nov 2013
Approximate Bayesian Computation for Smoothing James S. Martin Ajay Jasra Sumeetpal S. Singh N. Whiteley E. McCoy 58 25 0 22 Jun 2012
The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo Matthew D. Hoffman Andrew Gelman 165 4,300 0 18 Nov 2011
Expectation-Propagation for Likelihood-Free Inference Simon Barthelmé Nicolas Chopin 77 85 0 29 Jul 2011
Parameter Estimation for Hidden Markov Models with Intractable Likelihoods Elena Ehrlich Sumeetpal S. Singh Ajay Jasra N. Kantas TPM 92 92 0 28 Mar 2011
A Tutorial on Bayesian Optimization of Expensive Cost Functions, with Application to Active User Modeling and Hierarchical Reinforcement Learning E. Brochu Vlad M. Cora Nando de Freitas GP 136 2,447 0 12 Dec 2010
Likelihood-free Bayesian inference for alpha-stable models G. Peters Scott A. Sisson Yanan Fan 75 65 0 23 Dec 2009
Approximate Bayesian computation scheme for parameter inference and model selection in dynamical systems Tina Toni David Welch N. Strelkowa Andreas Ipsen M. Stumpf 242 1,547 0 14 Jan 2009