Tutorial and Survey on Probabilistic Graphical Model and Variational Inference in Deep Reinforcement Learning

25 August 2019

Papers citing "Tutorial and Survey on Probabilistic Graphical Model and Variational Inference in Deep Reinforcement Learning"

23 / 23 papers shown

Title
M-HOF-Opt: Multi-Objective Hierarchical Output Feedback Optimization via Multiplier Induced Loss Landscape Scheduling Xudong Sun Nutan Chen Alexej Gossmann Yu Xing Carla Feistner ... Felix Drost Daniele Scarcella Lisa Beer Carsten Marr Carsten Marr 64 1 0 20 Mar 2024
Variational Resampling Based Assessment of Deep Neural Networks under Distribution Shift Xudong Sun Alexej Gossmann Yu Wang B. Bischl OOD 53 5 0 07 Jun 2019
Maximum Entropy-Regularized Multi-Goal Reinforcement Learning Rui Zhao Xudong Sun Volker Tresp 50 82 0 21 May 2019
ReinBo: Machine Learning pipeline search and configuration with Bayesian Optimization embedded Reinforcement Learning Xudong Sun Jiali Lin B. Bischl AI4CE BDL TPM 37 11 0 10 Apr 2019
High Dimensional Restrictive Federated Model Selection with multi-objective Bayesian Optimization over shifted distributions Xudong Sun Andrea Bommert Florian Pfisterer Jörg Rahnenführer Michel Lang B. Bischl FedML 44 12 0 24 Feb 2019
Self-Consistent Trajectory Autoencoder: Hierarchical Reinforcement Learning with Trajectory Embeddings John D. Co-Reyes YuXuan Liu Abhishek Gupta Benjamin Eysenbach Pieter Abbeel Sergey Levine SSL BDL AIFin 55 145 0 07 Jun 2018
Reinforcement Learning and Control as Probabilistic Inference: Tutorial and Review Sergey Levine AI4CE BDL 73 671 0 02 May 2018
Efficient Model-Based Deep Reinforcement Learning with Variational State Tabulation Dane S. Corneil W. Gerstner Johanni Brea OffRL 53 62 0 12 Feb 2018
Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor Tuomas Haarnoja Aurick Zhou Pieter Abbeel Sergey Levine 284 8,313 0 04 Jan 2018
Proximal Policy Optimization Algorithms John Schulman Filip Wolski Prafulla Dhariwal Alec Radford Oleg Klimov OffRL 444 18,931 0 20 Jul 2017
Hindsight Experience Replay Marcin Andrychowicz Dwight Crow Alex Ray Jonas Schneider Rachel Fong Peter Welinder Bob McGrew Joshua Tobin Pieter Abbeel Wojciech Zaremba OffRL 242 2,322 0 05 Jul 2017
Reinforcement Learning with Deep Energy-Based Policies Tuomas Haarnoja Haoran Tang Pieter Abbeel Sergey Levine 92 1,339 0 27 Feb 2017
The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables Chris J. Maddison A. Mnih Yee Whye Teh BDL 159 2,529 0 02 Nov 2016
Tutorial on Variational Autoencoders Carl Doersch BDL DRL 94 1,741 0 19 Jun 2016
Asynchronous Methods for Deep Reinforcement Learning Volodymyr Mnih Adria Puigdomenech Badia M. Berk Mirza Alex Graves Timothy Lillicrap Tim Harley David Silver Koray Kavukcuoglu 189 8,833 0 04 Feb 2016
Variational Inference: A Review for Statisticians David M. Blei A. Kucukelbir Jon D. McAuliffe BDL 238 4,778 0 04 Jan 2016
Prioritized Experience Replay Tom Schaul John Quan Ioannis Antonoglou David Silver OffRL 210 3,787 0 18 Nov 2015
Deep Reinforcement Learning with Double Q-learning H. V. Hasselt A. Guez David Silver OffRL 156 7,623 0 22 Sep 2015
Continuous control with deep reinforcement learning Timothy Lillicrap Jonathan J. Hunt Alexander Pritzel N. Heess Tom Erez Yuval Tassa David Silver Daan Wierstra 302 13,214 0 09 Sep 2015
Weight Uncertainty in Neural Networks Charles Blundell Julien Cornebise Koray Kavukcuoglu Daan Wierstra UQCV BDL 169 1,886 0 20 May 2015
Trust Region Policy Optimization John Schulman Sergey Levine Philipp Moritz Michael I. Jordan Pieter Abbeel 271 6,755 0 19 Feb 2015
Auto-Encoding Variational Bayes Diederik P. Kingma Max Welling BDL 418 16,944 0 20 Dec 2013
Planning to Be Surprised: Optimal Bayesian Exploration in Dynamic Environments Yi Sun Faustino J. Gomez Jürgen Schmidhuber 99 163 0 29 Mar 2011