Pith. sign in

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

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T11:19:22.258041Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

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

  • verified exact3
  • verified fuzzy17
  • unresolved12
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

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

Resolution
unresolved
no resolver link, observed 2026-08-14T11:19:22.117550Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T11:19:22.117550Z digest=sha256:fdcddc53c68bd4a8fb16e5b9ea107111bc3d46453334c809858b084f5da855b6

Observation 34b5f5e6-372e-4ddb-bac8-8dd328139ddb · outbound

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:19:22.686059Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-14T11:19:22.122553Z digest=sha256:729f2c3b93409f205ef2e8d2e899e6a1f9afb372fae968f78a60b19873691a16

Observation 53a2da0f-3a21-46e5-9e5d-dca411c68370 · outbound

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:19:22.673094Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-14T11:19:22.126740Z digest=sha256:518d695a465a74633b14e3d0d89dc4f1423adcddd9f38f7f45ecbfca3a433e56

Observation 2cc04347-7b90-4337-a570-f6f916971ac7 · outbound

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:19:22.660322Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-14T11:19:22.132104Z digest=sha256:b9fbaf78071b7f56059f25680af137676f856cbb98fa49d048be0ec3eaa1a243

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

Resolution
verified exact
local_arxiv, observed 2026-08-14T11:19:22.444271Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-14T11:19:22.136207Z digest=sha256:4088fc269a09714dd8b98e68891af2e4e46343bebed04491cd268ef3ff41b45f

Observation e6f5fdb2-de3d-415d-a3d1-d15ab83a9570 · outbound

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:19:22.645681Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-14T11:19:22.141150Z digest=sha256:30234ae8f9709f866f27c8a020c3f37b9c39454b22652ba049d3dc01da76ebcd

Observation d53cf052-6c6a-41c5-a8a8-2dd427f24d8f · outbound

This paper cites an unresolved cited work.

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

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-14T11:19:22.145324Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T11:19:22.145324Z digest=sha256:6578a6346ad047dd9193ed25a20dda585c3bf2fe0f81ab8df818af60d7fa0d2f

Observation dfd5798b-fb44-406c-9277-41d060109ead · outbound

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:19:22.626002Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-14T11:19:22.149687Z digest=sha256:9d1e1f0cf06c62182f41804fb306e862f5bbe483713f80439d3e432a78131477

Observation 6f299b91-d757-4206-a01d-e356519420ee · outbound

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:19:22.613750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-14T11:19:22.153544Z digest=sha256:af3f71b6fac0cf378876d8b39b4e4ff8eb495501bc16206c406d14d82f545f78

Observation e671edd8-c719-4943-83b7-9db33f5a4844 · outbound

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

Resolution
unresolved
no resolver link, observed 2026-08-14T11:19:22.157313Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T11:19:22.157313Z digest=sha256:ee1b702b24691faadb397806d41a100fe06e5d139f47ed3acae48568c3d347d7

Observation 0244c9d1-6554-4c5e-9486-78b19a06b0a6 · outbound

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

Resolution
unresolved
no resolver link, observed 2026-08-14T11:19:22.162379Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T11:19:22.162379Z digest=sha256:428847ac6f8077b92f449b83b298037a5d16342478188deab87f399e998db5d2

Observation c16ceaad-eb0a-4329-a718-9a740044942e · outbound

This paper cites an unresolved cited work.

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

Reference 12

Resolution
unresolved
raw_fallback, observed 2026-08-14T11:19:22.601892Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-14T11:19:22.166439Z digest=sha256:d36e0db6627d021976633656fc883381e1d29e3fc39a1c5ad47f0e930b339e92

Observation adf0619e-39d0-4286-907a-a6c2e4bea36e · outbound

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

Resolution
unresolved
no resolver link, observed 2026-08-14T11:19:22.170282Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T11:19:22.170282Z digest=sha256:956cf4efd047e5d98e1a673d15f4afea973dbfe1343301ecdfdf366c52cd6b83

Observation 6c38d083-b9e3-49df-b5ff-9bce1ddc8171 · outbound

This paper cites Maximum Entropy-Regularized Multi-Goal Reinforcement Learning.

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

Reference 14

Resolution
verified exact
local_arxiv, observed 2026-08-14T11:19:22.391728Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-14T11:19:22.175142Z digest=sha256:c2b4ce4c68c206fa15934a318f7a247cf08cc46eef60fa4e7d5d3f4c4a4704a1

Observation becf7472-a3a8-4c5b-b9ec-963868d65af0 · outbound

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:19:22.589390Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-14T11:19:22.179785Z digest=sha256:a1d4f5b1c1ad30e4ccc168abefb49aba58c6030df5f029bf811709db49e8145b

Observation 5bb0a6e7-4049-4450-b4a9-f4614149ede5 · outbound

This paper cites Deep reinforcement learning with double q-learning,.

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

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:19:22.576565Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-14T11:19:22.184607Z digest=sha256:b9858e12d6f52c541a32715f6eff326a74e4ac0ae63406afdcefe589caff9d94

Observation 4146b11f-dc4a-4dc9-b748-3b2e4d6ffc43 · outbound

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

Resolution
unresolved
no resolver link, observed 2026-08-14T11:19:22.188655Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T11:19:22.188655Z digest=sha256:b79eff82c9baa253cd355970952a02808647d732e7c9b375d99c4f2586c9c743

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:19:22.564144Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-14T11:19:22.193027Z digest=sha256:5c00db8b8dc59c1dbb5c9866cc89a9fe39c516a91ed71f112080855cd470dbad

Observation de38d8af-4da1-40b4-aa69-57099354f489 · outbound

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:19:22.551686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-14T11:19:22.198384Z digest=sha256:8f9e40810ce3f90f32987b1e49ece842108acbeccbfbcbc98f66e692bb75bc88

Observation d46e569f-c7f0-47f0-a7f7-c1f1708b7922 · outbound

This paper cites Proximal Policy Optimization Algorithms.

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

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-14T11:19:22.205452Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T11:19:22.205452Z digest=sha256:82e14aabce73a11af06cf9bf13c075b41df815341fdfe8d731605250877d0f1b

Observation a03113c0-a74d-421c-99fd-a166347e0eea · outbound

This paper cites Universal value func- tion approximators,.

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

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:19:22.538966Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-14T11:19:22.209774Z digest=sha256:1896e116ad98d5c789ea708dcb597b1acb482113786cba7f1d0cbbaa4bfeea13

Observation 2eff6a1b-a1a1-428e-9d13-d5fa9c0f86f9 · outbound

This paper cites A lesson learned from pmf based approach for semantic recommender system,.

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:19:22.526526Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-14T11:19:22.214195Z digest=sha256:204fa52aea89c0754fa64afa8204a3d850eb838f6bdef7dd1afe79031d3a02fb

Observation 789a2179-8c90-4868-ab45-91948c70252c · outbound

This paper cites Hindsight expe- rience replay,.

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

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:19:22.512790Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-14T11:19:22.219314Z digest=sha256:b6546fb5e12108bf99d858587c6b2ab742aa3c68c6408af203751dc15f91290e

Observation f613ccfc-5be1-4db7-a5f3-21f3190ec92e · outbound

This paper cites Prioritized Experience Replay.

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

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-14T11:19:22.223090Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T11:19:22.223090Z digest=sha256:8cd9290025eb496246a21d2a2da233321f75a82d9128e569309d6b10ce064d66

Observation ba713fd5-f5fb-41cd-bb43-8c1caa94f65c · outbound

This paper cites High Dimensional Restrictive Federated Model Selection with multi-objective Bayesian Optimization over shifted distributions.

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

Resolution
verified exact
local_arxiv, observed 2026-08-14T11:19:22.337324Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-14T11:19:22.228167Z digest=sha256:49fce8a664d99e5d7987e9843334d0c2a3232e2642b5e8803cf9d5f3f9cfdc18

Observation e675ed03-0f6f-4d51-a434-eff06c9c4c33 · outbound

This paper cites Approximately optimal approximate rein- forcement learning,.

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

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:19:22.499711Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-14T11:19:22.232519Z digest=sha256:f1d8dfef4e69c567a47a4a3818a2ec40789fd103372b0ca3809a5930d6d6c27f

Observation 1383a316-daf6-45af-a4c5-a5ee9772ac7b · outbound

This paper cites Reinforcement learning with factored states and actions,.

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

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:19:22.485712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-14T11:19:22.236441Z digest=sha256:0b118ec81fca5e48e3d6bdd94ffa07341200b7dde5b41aa2b66a11e267b61e12

Observation 79c8de57-6c8f-4e53-82ad-4164d9c9056d · outbound

This paper cites Reinforcement learning with deep energy-based policies,.

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

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:19:22.471133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-14T11:19:22.240764Z digest=sha256:4b5069349088a18e1b6fc7bce422f380da956614a8db8de6807ff19f23c18ffe

Observation 3bb557b2-a664-48f6-939e-f77348bd19aa · outbound

This paper cites Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor.

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

Resolution
unresolved
no resolver link, observed 2026-08-14T11:19:22.245109Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T11:19:22.245109Z digest=sha256:e1774997e28c6f1848d96f3c0ce722c4e4bdf74b3a28362ac12865c467ca9c2f

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T11:19:22.457839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-14T11:19:22.249723Z digest=sha256:3266fa53381bc65a4020cd4d0195f8bbc66d119049c6904a42b71d44adda7c74

Observation ec8bc9f9-11c1-4d54-9c1b-592add75a74f · outbound

This paper cites Tutorial on Variational Autoencoders.

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

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-14T11:19:22.254123Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T11:19:22.254123Z digest=sha256:2d23ba4e6c69b088e94ab76a932af7cab4f60a3ce8882f7a1459037a1be7d050

Observation ef9ad3b4-f4fe-42ad-bb96-f545b5c510d4 · outbound

This paper cites The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables.

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

Resolution
unresolved
no resolver link, observed 2026-08-14T11:19:22.258041Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T11:19:22.258041Z digest=sha256:238a5940a079b7bb04363780e3b0c4f95ebe015442ba722e0b188dd2069b9454

Pith citing papers

No inbound Pith citation observations are available.