Black box variational inference for state space models

23 November 2015

Papers citing "Black box variational inference for state space models"

31 / 31 papers shown

Title
Modeling Latent Neural Dynamics with Gaussian Process Switching Linear Dynamical Systems Amber Hu D. Zoltowski Aditya Nair David Anderson Lea Duncker Scott W. Linderman 36 3 0 19 Jul 2024
Provably Scalable Black-Box Variational Inference with Structured Variational Families Joohwan Ko Kyurae Kim W. Kim Jacob R. Gardner BDL 33 2 0 19 Jan 2024
Efficient variational approximations for state space models Rubén Loaiza-Maya D. Nibbering 6 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
Tractable Dendritic RNNs for Reconstructing Nonlinear Dynamical Systems Manuela Brenner Florian Hess Jonas M. Mikhaeil Leonard Bereska Zahra Monfared Po-Chen Kuo Daniel Durstewitz AI4CE 37 29 0 06 Jul 2022
GD-VAEs: Geometric Dynamic Variational Autoencoders for Learning Nonlinear Dynamics and Dimension Reductions Ryan Lopez P. Atzberger AI4CE 26 8 0 10 Jun 2022
Reconstructing Nonlinear Dynamical Systems from Multi-Modal Time Series Daniel Kramer P. Bommer Carlo Tombolini G. Koppe Daniel Durstewitz BDL AI4TS AI4CE 25 19 0 04 Nov 2021
Online Variational Filtering and Parameter Learning Andrew Campbell Yuyang Shi Tom Rainforth Arnaud Doucet BDL 30 21 0 26 Oct 2021
Unsupervised Learned Kalman Filtering Guy Revach Nir Shlezinger Timur Locher Xiaoyong Ni Ruud J. G. van Sloun Yonina C. Eldar SSL 31 31 0 18 Oct 2021
KalmanNet: Neural Network Aided Kalman Filtering for Partially Known Dynamics Guy Revach Nir Shlezinger Xiaoyong Ni Adrià López Escoriza Ruud J. G. van Sloun Yonina C. Eldar 31 264 0 21 Jul 2021
Differentiable Particle Filtering via Entropy-Regularized Optimal Transport Adrien Corenflos James Thornton George Deligiannidis Arnaud Doucet OT 43 66 0 15 Feb 2021
Physics-aware, probabilistic model order reduction with guaranteed stability Sebastian Kaltenbach P. Koutsourelakis DiffM AI4CE 16 15 0 14 Jan 2021
Efficient Model-Based Reinforcement Learning through Optimistic Policy Search and Planning Sebastian Curi Felix Berkenkamp Andreas Krause 33 82 0 15 Jun 2020
The Neural Moving Average Model for Scalable Variational Inference of State Space Models Tom Ryder D. Prangle Andrew Golightly Isaac Matthews BDL AI4TS 16 6 0 02 Oct 2019
Particle Smoothing Variational Objectives A. Moretti Zizhao Wang Luhuan Wu Iddo Drori I. Pe’er 24 10 0 20 Sep 2019
Stochastic Latent Actor-Critic: Deep Reinforcement Learning with a Latent Variable Model Alex X. Lee Anusha Nagabandi Pieter Abbeel Sergey Levine OffRL BDL 25 372 0 01 Jul 2019
Neural Dynamics Discovery via Gaussian Process Recurrent Neural Networks Qi She Anqi Wu BDL 20 34 0 01 Jul 2019
Recurrent Kalman Networks: Factorized Inference in High-Dimensional Deep Feature Spaces P. Becker Harit Pandya Gregor H. W. Gebhardt Cheng Zhao James Taylor Gerhard Neumann BDL 13 94 0 17 May 2019
Bidirectional Inference Networks: A Class of Deep Bayesian Networks for Health Profiling Hao Wang Chengzhi Mao Hao He Mingmin Zhao Tommi Jaakkola Dina Katabi BDL 24 22 0 06 Feb 2019
Temporal Difference Variational Auto-Encoder Karol Gregor George Papamakarios F. Besse Lars Buesing Theophane Weber DRL 24 126 0 08 Jun 2018
Scalable Bayesian Learning for State Space Models using Variational Inference with SMC Samplers Marcel Hirt P. Dellaportas BDL 20 10 0 23 May 2018
Learning Awareness Models Brandon Amos Laurent Dinh Serkan Cabi Thomas Rothörl Sergio Gomez Colmenarejo Alistair Muldal Tom Erez Yuval Tassa Nando de Freitas Misha Denil 23 44 0 17 Apr 2018
Variational Message Passing with Structured Inference Networks Wu Lin Nicolas Hubacher Mohammad Emtiyaz Khan BDL 23 54 0 15 Mar 2018
Black-box Variational Inference for Stochastic Differential Equations Tom Ryder Andrew Golightly A. Mcgough D. Prangle 16 57 0 09 Feb 2018
Gaussian variational approximation for high-dimensional state space models M. Quiroz David J. Nott Robert Kohn 24 40 0 24 Jan 2018
Stochastic Sequential Neural Networks with Structured Inference Hao Liu Haoli Bai Lirong He Zenglin Xu BDL 23 3 0 24 May 2017
Structured Inference Networks for Nonlinear State Space Models Rahul G. Krishnan Uri Shalit David Sontag BDL 16 452 0 30 Sep 2016
Linear dynamical neural population models through nonlinear embeddings Yuanjun Gao Evan Archer Liam Paninski John P. Cunningham 16 155 0 26 May 2016
Sequential Neural Models with Stochastic Layers Marco Fraccaro Søren Kaae Sønderby Ulrich Paquet Ole Winther BDL 65 393 0 24 May 2016
Gaussian variational approximation with sparse precision matrices Linda S. L. Tan David J. Nott 30 76 0 18 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 22 482 0 20 Mar 2016