Deep Kalman Filters

16 November 2015

Papers citing "Deep Kalman Filters"

33 / 83 papers shown

Title
GRU-ODE-Bayes: Continuous modeling of sporadically-observed time series E. Brouwer Jaak Simm Adam Arany Yves Moreau SyDa CML AI4TS 45 290 0 29 May 2019
Deep Factors for Forecasting Bernie Wang Alex Smola Danielle C. Maddix Jan Gasthaus Dean Phillips Foster Tim Januschowski BDL 24 170 0 28 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
Deconfounding Reinforcement Learning in Observational Settings Chaochao Lu Bernhard Schölkopf José Miguel Hernández-Lobato CML OOD 30 73 0 26 Dec 2018
Deep Factors with Gaussian Processes for Forecasting Danielle C. Maddix Bernie Wang Alex Smola BDL UQCV AI4TS 33 41 0 30 Nov 2018
Learning Attractor Dynamics for Generative Memory Yan Wu Greg Wayne Karol Gregor Timothy Lillicrap BDL 19 18 0 23 Nov 2018
Deep Generative Video Compression Jun Han Salvator Lombardo Christopher Schroers Stephan Mandt VGen 32 58 0 05 Oct 2018
Socially Aware Kalman Neural Networks for Trajectory Prediction Ce Ju Zheng Wang Xiaoyu Zhang 33 8 0 14 Sep 2018
Variational Inference for Data-Efficient Model Learning in POMDPs Sebastian Tschiatschek Kai Arulkumaran Jan Stühmer Katja Hofmann 24 15 0 23 May 2018
Approximate Bayesian inference in spatial environments Atanas Mirchev Baris Kayalibay Maximilian Soelch Patrick van der Smagt Justin Bayer BDL 16 22 0 18 May 2018
Spatio-Temporal Neural Networks for Space-Time Series Forecasting and Relations Discovery Ali Ziat E. Delasalles Ludovic Denoyer Patrick Gallinari BDL AI4TS AI4CE 28 74 0 23 Apr 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 29 44 0 17 Apr 2018
Probabilistic Video Generation using Holistic Attribute Control Jiawei He Andreas M. Lehrmann Joseph Marino Greg Mori Leonid Sigal VGen DiffM DRL 22 77 0 21 Mar 2018
Ocean Eddy Identification and Tracking using Neural Networks K. Franz R. Roscher Andres Milioto Susanne Wenzel J. Kusche AI4Cl 28 69 0 20 Mar 2018
Variational Message Passing with Structured Inference Networks Wu Lin Nicolas Hubacher Mohammad Emtiyaz Khan BDL 28 54 0 15 Mar 2018
Stochastic Video Generation with a Learned Prior Emily L. Denton Rob Fergus VGen 48 525 0 21 Feb 2018
State Representation Learning for Control: An Overview Timothée Lesort Natalia Díaz Rodríguez Jean-François Goudou David Filliat OffRL 28 319 0 12 Feb 2018
Advances in Variational Inference Cheng Zhang Judith Butepage Hedvig Kjellström Stephan Mandt BDL 38 684 0 15 Nov 2017
From Deterministic to Generative: Multi-Modal Stochastic RNNs for Video Captioning Jingkuan Song Yuyu Guo Lianli Gao Xuelong Li Alan Hanjalic Heng Tao Shen 40 219 0 08 Aug 2017
Long Short-Term Memory Kalman Filters:Recurrent Neural Estimators for Pose Regularization Huseyin Coskun F. Achilles R. DiPietro Nassir Navab Federico Tombari 30 162 0 06 Aug 2017
Stochastic Sequential Neural Networks with Structured Inference Hao Liu Haoli Bai Lirong He Zenglin Xu BDL 23 3 0 24 May 2017
Clinical Intervention Prediction and Understanding using Deep Networks Harini Suresh Nathan Hunt Alistair E. W. Johnson Leo Anthony Celi Peter Szolovits Marzyeh Ghassemi OOD 33 131 0 23 May 2017
The Kernel Mixture Network: A Nonparametric Method for Conditional Density Estimation of Continuous Random Variables L. Ambrogioni Umut Güçlü Marcel van Gerven E. Maris BDL 35 47 0 19 May 2017
Learning to Represent Haptic Feedback for Partially-Observable Tasks Jaeyong Sung J. Salisbury Ashutosh Saxena SSL 25 32 0 17 May 2017
Semi-Supervised Generation with Cluster-aware Generative Models Lars Maaløe Marco Fraccaro Ole Winther 23 28 0 03 Apr 2017
Towards Lifelong Self-Supervision: A Deep Learning Direction for Robotics J. M. Wong 27 11 0 01 Nov 2016
Deep Amortized Inference for Probabilistic Programs Daniel E. Ritchie Paul Horsfall Noah D. Goodman TPM 24 81 0 18 Oct 2016
Structured Inference Networks for Nonlinear State Space Models Rahul G. Krishnan Uri Shalit David Sontag BDL 22 452 0 30 Sep 2016
LFADS - Latent Factor Analysis via Dynamical Systems David Sussillo Rafal Jozefowicz L. F. Abbott C. Pandarinath AI4CE 32 89 0 22 Aug 2016
Linear dynamical neural population models through nonlinear embeddings Yuanjun Gao Evan Archer Liam Paninski John P. Cunningham 21 155 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
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 27 482 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 34 160 0 23 Nov 2015