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Paper Citation Record · LEDGER

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

As of 18 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:1908.09381.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
1908.09381 v5

Coverage vector

measured 32 of 32 reference resolution

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measured 32 of 32 standing notices

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

32 of 32 outbound references displayed

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External citation measurements

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Outbound references

Observation 41a56b4a-69c0-41d5-8ced-f58852a50236 · outbound

This paper cites Human-level control through deep reinforcement learning,.

Tutorial and Survey on Probabilistic Graphical Model and Variational Inference in Deep Reinforcement Learning Human-level control through deep reinforcement learning,

Reference 1

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This paper cites Trust region policy optimization,.

Tutorial and Survey on Probabilistic Graphical Model and Variational Inference in Deep Reinforcement Learning Trust region policy optimization,

Reference 2

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This paper cites Reinbo: Machine learning pipeline search and configuration with bayesian optimization embedded reinforcement learning,.

Tutorial and Survey on Probabilistic Graphical Model and Variational Inference in Deep Reinforcement Learning Reinbo: Machine learning pipeline search and configuration with bayesian optimization embedded reinforcement learning,

Reference 3

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This paper cites Vime: Variational information maximizing exploration,.

Tutorial and Survey on Probabilistic Graphical Model and Variational Inference in Deep Reinforcement Learning Vime: Variational information maximizing exploration,

Reference 4

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Observation 517e7983-3f4e-4858-a0ba-af5fa8867c7f · outbound

This paper cites Efficient Model-Based Deep Reinforcement Learning with Variational State Tabulation.

Tutorial and Survey on Probabilistic Graphical Model and Variational Inference in Deep Reinforcement Learning Efficient Model-Based Deep Reinforcement Learning with Variational State Tabulation

Reference 5

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This paper cites Variational inference: A review for statisticians,.

Tutorial and Survey on Probabilistic Graphical Model and Variational Inference in Deep Reinforcement Learning Variational inference: A review for statisticians,

Reference 6

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

Reference 7

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This paper cites Training restricted boltzmann machines: An introduction,.

Tutorial and Survey on Probabilistic Graphical Model and Variational Inference in Deep Reinforcement Learning Training restricted boltzmann machines: An introduction,

Reference 8

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This paper cites Variational resampling based assessment of deep neural networks under distribution shift,.

Tutorial and Survey on Probabilistic Graphical Model and Variational Inference in Deep Reinforcement Learning Variational resampling based assessment of deep neural networks under distribution shift,

Reference 9

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This paper cites Weight Uncertainty in Neural Networks.

Tutorial and Survey on Probabilistic Graphical Model and Variational Inference in Deep Reinforcement Learning Weight Uncertainty in Neural Networks

Reference 10

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This paper cites Auto-Encoding Variational Bayes.

Tutorial and Survey on Probabilistic Graphical Model and Variational Inference in Deep Reinforcement Learning Auto-Encoding Variational Bayes

Reference 11

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

Reference 12

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This paper cites Reinforcement Learning and Control as Probabilistic Inference: Tutorial and Review.

Tutorial and Survey on Probabilistic Graphical Model and Variational Inference in Deep Reinforcement Learning Reinforcement Learning and Control as Probabilistic Inference: Tutorial and Review

Reference 13

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Tutorial and Survey on Probabilistic Graphical Model and Variational Inference in Deep Reinforcement Learning Maximum Entropy-Regularized Multi-Goal Reinforcement Learning

Reference 14

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This paper cites Planning and acting in partially observable stochastic domains,.

Tutorial and Survey on Probabilistic Graphical Model and Variational Inference in Deep Reinforcement Learning Planning and acting in partially observable stochastic domains,

Reference 15

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Tutorial and Survey on Probabilistic Graphical Model and Variational Inference in Deep Reinforcement Learning Deep reinforcement learning with double q-learning,

Reference 16

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This paper cites Continuous control with deep reinforcement learning.

Tutorial and Survey on Probabilistic Graphical Model and Variational Inference in Deep Reinforcement Learning Continuous control with deep reinforcement learning

Reference 17

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Observation 7c751d78-5642-462c-bc5f-192e700db089 · outbound

This paper cites Deterministic policy gradient algorithms,.

Tutorial and Survey on Probabilistic Graphical Model and Variational Inference in Deep Reinforcement Learning Deterministic policy gradient algorithms,

Reference 18

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This paper cites Asynchronous methods for deep rein- forcement learning,.

Tutorial and Survey on Probabilistic Graphical Model and Variational Inference in Deep Reinforcement Learning Asynchronous methods for deep rein- forcement learning,

Reference 19

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Tutorial and Survey on Probabilistic Graphical Model and Variational Inference in Deep Reinforcement Learning Proximal Policy Optimization Algorithms

Reference 20

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Tutorial and Survey on Probabilistic Graphical Model and Variational Inference in Deep Reinforcement Learning Universal value func- tion approximators,

Reference 21

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Tutorial and Survey on Probabilistic Graphical Model and Variational Inference in Deep Reinforcement Learning A lesson learned from pmf based approach for semantic recommender system,

Reference 22

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Tutorial and Survey on Probabilistic Graphical Model and Variational Inference in Deep Reinforcement Learning Hindsight expe- rience replay,

Reference 23

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

Reference 24

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Tutorial and Survey on Probabilistic Graphical Model and Variational Inference in Deep Reinforcement Learning High Dimensional Restrictive Federated Model Selection with multi-objective Bayesian Optimization over shifted distributions

Reference 25

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Tutorial and Survey on Probabilistic Graphical Model and Variational Inference in Deep Reinforcement Learning Approximately optimal approximate rein- forcement learning,

Reference 26

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Tutorial and Survey on Probabilistic Graphical Model and Variational Inference in Deep Reinforcement Learning Reinforcement learning with factored states and actions,

Reference 27

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Tutorial and Survey on Probabilistic Graphical Model and Variational Inference in Deep Reinforcement Learning Reinforcement learning with deep energy-based policies,

Reference 28

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Tutorial and Survey on Probabilistic Graphical Model and Variational Inference in Deep Reinforcement Learning Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor

Reference 29

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Observation 388e9c4e-827e-454b-89ce-7b7ad724140a · outbound

This paper cites Planning to be surprised: Op- timal bayesian exploration in dynamic environments,.

Tutorial and Survey on Probabilistic Graphical Model and Variational Inference in Deep Reinforcement Learning Planning to be surprised: Op- timal bayesian exploration in dynamic environments,

Reference 30

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

Reference 31

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Tutorial and Survey on Probabilistic Graphical Model and Variational Inference in Deep Reinforcement Learning The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables

Reference 32

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