v1v2 (latest)

Efficient Amortised Bayesian Inference for Hierarchical and Nonlinear Dynamical Systems

28 May 2019

ArXiv (abs)PDF HTML Github (47★)

Papers citing "Efficient Amortised Bayesian Inference for Hierarchical and Nonlinear Dynamical Systems"

20 / 20 papers shown

Title
Amortized Bayesian Multilevel Models Daniel Habermann Marvin Schmitt Lars Kühmichel Andreas Bulling Stefan T. Radev Paul-Christian Bürkner 235 4 0 23 Aug 2024
GD-VAEs: Geometric Dynamic Variational Autoencoders for Learning Nonlinear Dynamics and Dimension Reductions Ryan Lopez P. Atzberger AI4CE 86 8 0 10 Jun 2022
Doubly Reparameterized Gradient Estimators for Monte Carlo Objectives George Tucker Dieterich Lawson S. Gu Chris J. Maddison BDL 76 110 0 09 Oct 2018
Neural Ordinary Differential Equations T. Chen Yulia Rubanova J. Bettencourt David Duvenaud AI4CE 457 5,168 0 19 Jun 2018
Tighter Variational Bounds are Not Necessarily Better Tom Rainforth Adam R. Kosiorek T. Le Chris J. Maddison Maximilian Igl Frank Wood Yee Whye Teh DRL 184 198 0 13 Feb 2018
Black-box Variational Inference for Stochastic Differential Equations Tom Ryder Andrew Golightly A. Mcgough D. Prangle 82 58 0 09 Feb 2018
Scalable Variational Inference for Dynamical Systems Nico S. Gorbach Stefan Bauer J. M. Buhmann BDL 57 49 0 19 May 2017
Recurrent switching linear dynamical systems Scott W. Linderman Andrew C. Miller Ryan P. Adams David M. Blei Liam Paninski Matthew J. Johnson 113 73 0 26 Oct 2016
Automatic chemical design using a data-driven continuous representation of molecules Rafael Gómez-Bombarelli Jennifer N. Wei David Duvenaud José Miguel Hernández-Lobato Benjamín Sánchez-Lengeling Dennis Sheberla J. Aguilera-Iparraguirre Timothy D. Hirzel Ryan P. Adams Alán Aspuru-Guzik 3DV 180 2,945 0 07 Oct 2016
Automatic Variational ABC Alexander Moreno T. Adel Edward Meeds James M. Rehg Max Welling 166 12 0 28 Jun 2016
Linear dynamical neural population models through nonlinear embeddings Yuanjun Gao Evan Archer Liam Paninski John P. Cunningham 84 155 0 26 May 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 57 375 0 20 May 2016
Composing graphical models with neural networks for structured representations and fast inference Matthew J. Johnson David Duvenaud Alexander B. Wiltschko S. R. Datta Ryan P. Adams BDL OCL 92 485 0 20 Mar 2016
Black box variational inference for state space models Evan Archer Il Memming Park Lars Buesing John P. Cunningham Liam Paninski BDL 83 161 0 23 Nov 2015
Deep Kalman Filters Rahul G. Krishnan Uri Shalit David Sontag BDL AI4TS 77 374 0 16 Nov 2015
Importance Weighted Autoencoders Yuri Burda Roger C. Grosse Ruslan Salakhutdinov BDL 282 1,246 0 01 Sep 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 2.1K 150,433 0 22 Dec 2014
Auto-Encoding Variational Bayes Diederik P. Kingma Max Welling BDL 484 16,922 0 20 Dec 2013
Stochastic Variational Inference Matt Hoffman David M. Blei Chong-Jun Wang John Paisley BDL 277 2,628 0 29 Jun 2012
Approximate Bayesian computation scheme for parameter inference and model selection in dynamical systems Tina Toni David Welch N. Strelkowa Andreas Ipsen M. Stumpf 261 1,552 0 14 Jan 2009