State Space LSTM Models with Particle MCMC Inference

30 November 2017

Papers citing "State Space LSTM Models with Particle MCMC Inference"

9 / 9 papers shown

Title
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 42 30 0 06 Jul 2022
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 31 266 0 21 Jul 2021
RNN with Particle Flow for Probabilistic Spatio-temporal Forecasting Soumyasundar Pal Liheng Ma Yingxue Zhang Mark J. Coates BDL AI4TS 33 22 0 10 Jun 2021
Variational Dynamic Mixtures Chen Qiu Stephan Mandt Maja R. Rudolph BDL AI4TS 16 2 0 20 Oct 2020
Sequential Neural Processes Gautam Singh Jaesik Yoon Youngsung Son Sungjin Ahn BDL AI4TS 40 81 0 24 Jun 2019
Deep Factors for Forecasting Bernie Wang Alex Smola Danielle C. Maddix Jan Gasthaus Dean Phillips Foster Tim Januschowski BDL 21 170 0 28 May 2019
Particle-based pedestrian path prediction using LSTM-MDL models Ronny Hug S. Becker Wolfgang Hubner Michael Arens 41 32 0 16 Apr 2018