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Interpretable Latent Variables in Deep State Space Models

3 March 2022

Papers citing "Interpretable Latent Variables in Deep State Space Models"

26 / 26 papers shown

Title
Deep State-Space Generative Model For Correlated Time-to-Event Predictions Yuan Xue Denny Zhou Nan Du Andrew M. Dai Zhen Xu Kun Zhang Claire Cui 118 8 0 28 Jul 2024
Learning Interpretable Deep State Space Model for Probabilistic Time Series Forecasting Longyuan Li Junchi Yan Xiaokang Yang Yaohui Jin OOD BDL AI4TS 80 63 0 31 Jan 2021
Deep State Space Models for Nonlinear System Identification Daniel Gedon Niklas Wahlström Thomas B. Schon L. Ljung 43 88 0 31 Mar 2020
Temporal Fusion Transformers for Interpretable Multi-horizon Time Series Forecasting Bryan Lim Sercan O. Arik Nicolas Loeff Tomas Pfister AI4TS 118 1,469 0 19 Dec 2019
Horseshoe Regularization for Machine Learning in Complex and Deep Models A. Bhadra J. Datta Yunfan Li Nicholas G. Polson 46 15 0 24 Apr 2019
Structured Variational Learning of Bayesian Neural Networks with Horseshoe Priors S. Ghosh Jiayu Yao Finale Doshi-Velez BDL UQCV 48 78 0 13 Jun 2018
Forecasting Economics and Financial Time Series: ARIMA vs. LSTM Sima Siami‐Namini A. Namin AI4TS 58 226 0 16 Mar 2018
Z-Forcing: Training Stochastic Recurrent Networks Anirudh Goyal Alessandro Sordoni Marc-Alexandre Côté Nan Rosemary Ke Yoshua Bengio BDL 70 185 0 15 Nov 2017
The Inverse Gamma-Gamma Prior for Optimal Posterior Contraction and Multiple Hypothesis Testing Ray Bai M. Ghosh 33 7 0 12 Oct 2017
Model Selection in Bayesian Neural Networks via Horseshoe Priors S. Ghosh Finale Doshi-Velez BDL 67 120 0 29 May 2017
Bayesian Compression for Deep Learning Christos Louizos Karen Ullrich Max Welling UQCV BDL 166 481 0 24 May 2017
DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks David Salinas Valentin Flunkert Jan Gasthaus AI4TS UQCV BDL 81 2,123 0 13 Apr 2017
Multiplicative Normalizing Flows for Variational Bayesian Neural Networks Christos Louizos Max Welling BDL 152 462 0 06 Mar 2017
PixelVAE: A Latent Variable Model for Natural Images Ishaan Gulrajani Kundan Kumar Faruk Ahmed Adrien Ali Taïga Francesco Visin David Vazquez Aaron Courville DRL SSL BDL 80 340 0 15 Nov 2016
Variational Lossy Autoencoder Xi Chen Diederik P. Kingma Tim Salimans Yan Duan Prafulla Dhariwal John Schulman Ilya Sutskever Pieter Abbeel DRL SSL GAN 152 676 0 08 Nov 2016
Structured Inference Networks for Nonlinear State Space Models Rahul G. Krishnan Uri Shalit David Sontag BDL 93 459 0 30 Sep 2016
Sequential Neural Models with Stochastic Layers Marco Fraccaro Søren Kaae Sønderby Ulrich Paquet Ole Winther BDL 117 398 0 24 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 53 0 0 20 May 2016
Variational Inference for Sparse and Undirected Models John Ingraham D. Marks 90 8 0 11 Feb 2016
Generating Sentences from a Continuous Space Samuel R. Bowman Luke Vilnis Oriol Vinyals Andrew M. Dai Rafal Jozefowicz Samy Bengio DRL 113 2,364 0 19 Nov 2015
Deep Kalman Filters Rahul G. Krishnan Uri Shalit David Sontag BDL AI4TS 73 374 0 16 Nov 2015
A Recurrent Latent Variable Model for Sequential Data Junyoung Chung Kyle Kastner Laurent Dinh Kratarth Goel Aaron Courville Yoshua Bengio DRL BDL 90 1,261 0 07 Jun 2015
Variational Inference with Normalizing Flows Danilo Jimenez Rezende S. Mohamed DRL BDL 318 4,197 0 21 May 2015
Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling Junyoung Chung Çağlar Gülçehre Kyunghyun Cho Yoshua Bengio 598 12,734 0 11 Dec 2014
Learning Stochastic Recurrent Networks Justin Bayer Christian Osendorfer BDL 78 274 0 27 Nov 2014
Auto-Encoding Variational Bayes Diederik P. Kingma Max Welling BDL 455 16,923 0 20 Dec 2013