Paper Citation Record · LEDGER

EVaDE : Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning

As of 21 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 0 inbound Pith citation observations for arXiv:2501.09611.

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

pith.paper-citation-record.v1
2501.09611 v1

Coverage vector

measured 45 of 45 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T19:55:36.053274Z

measured 45 of 45 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

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

45 of 45 outbound references displayed

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External citation measurements

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Outbound references

Observation 3c9d7ef1-1277-49e7-b42a-5512854fa1f4 · outbound

This paper cites Deep Reinforcement Learning at the Edge of the Statistical Precipice.

EVaDE : Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning Deep Reinforcement Learning at the Edge of the Statistical Precipice

Reference 1

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Observation b6754f36-cb55-4b71-a168-0b2094679865 · outbound

This paper cites Optimistic Posterior Sampling for Reinforcement Learning: Worst-Case Regret Bounds.

EVaDE : Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning Optimistic Posterior Sampling for Reinforcement Learning: Worst-Case Regret Bounds

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:55:36.556779Z

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Observation 2d3b2cae-5733-4431-8455-f41cfa77d442 · outbound

This paper cites State-Aware Variational Thompson Sampling for Deep Q-Networks.

EVaDE : Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning State-Aware Variational Thompson Sampling for Deep Q-Networks

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:55:36.546893Z

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Observation b62440ba-6fa3-4898-9788-5e8dc3b96899 · outbound

This paper cites Efficient Exploration through Bayesian Deep Q- Networks.

EVaDE : Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning Efficient Exploration through Bayesian Deep Q- Networks

Reference 4

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Observation 9c906764-9496-4073-86e1-c5c11d07e841 · outbound

This paper cites Campbell, and Sergey Levine.

EVaDE : Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning Campbell, and Sergey Levine

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:55:36.526199Z

Source-reported events for the cited work

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Observation 47e0cfef-0713-421d-abc6-3240d1cabc59 · outbound

This paper cites Unifying Count-Based Explo- ration and Intrinsic Motivation.

EVaDE : Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning Unifying Count-Based Explo- ration and Intrinsic Motivation

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:55:36.515967Z

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Observation 3911ed0d-f654-4491-839e-069a8661d874 · outbound

This paper cites Path Integral Guided Policy Search.

EVaDE : Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning Path Integral Guided Policy Search

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:55:36.505150Z

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Observation 94a89d7f-b0ad-46b5-aab9-716f0b2e134d · outbound

This paper cites Efficient Selectivity and Backup Operators in Monte-Carlo Tree Search.

EVaDE : Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning Efficient Selectivity and Backup Operators in Monte-Carlo Tree Search

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:55:36.494403Z

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Observation 4ff8066b-a52f-464b-8ba5-f5194da92c20 · outbound

This paper cites Efficient Model-Based Reinforcement Learning through Optimistic Policy Search and Planning.

EVaDE : Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning Efficient Model-Based Reinforcement Learning through Optimistic Policy Search and Planning

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:55:36.482103Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 79540c1f-c4d6-434f-b876-7135487f73b9 · outbound

This paper cites Noisy Networks for Exploration.

EVaDE : Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning Noisy Networks for Exploration

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:55:36.469782Z

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Observation 2afb9886-7567-4765-b58a-4339e86e892d · outbound

This paper cites Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning.

EVaDE : Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:55:36.458126Z

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Observation a7ed6cfa-5fef-422f-9d3d-b0cdc602125c · outbound

This paper cites T emporal Difference Variational Auto-Encoder.

EVaDE : Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning T emporal Difference Variational Auto-Encoder

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:55:36.446680Z

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Observation 1ba54c0f-8fb2-434a-812a-65472681390f · outbound

This paper cites Recurrent World Models Facilitate Policy Evolution.

EVaDE : Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning Recurrent World Models Facilitate Policy Evolution

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:55:36.435816Z

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Observation 0c75bf1e-9bce-42f8-879f-7625e0e10b29 · outbound

This paper cites Learning Latent Dynamics for Planning from Pixels.

EVaDE : Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning Learning Latent Dynamics for Planning from Pixels

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:55:36.423977Z

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Observation 9039ec38-4961-4629-9880-ddc0abe72d25 · outbound

This paper cites Harris, K.

EVaDE : Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning Harris, K

Reference 16

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Source-reported events for the cited work

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Observation c1817ba5-d31d-4e8b-9f5e-7fcf1a75eeac · outbound

This paper cites Deep reinforcement learning that matters.

EVaDE : Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning Deep reinforcement learning that matters

Reference 17

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Source-reported events for the cited work

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Observation c3f814c6-7c94-4af6-9b1f-049a7a79a48b · outbound

This paper cites Near-Optimal Regret Bounds for Reinforcement Learning.

EVaDE : Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning Near-Optimal Regret Bounds for Reinforcement Learning

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:55:36.400437Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 59abbed8-df8b-4879-82e4-c999e0097802 · outbound

This paper cites Importance of using appropriate baselines for evaluation of data-efficiency in deep reinforcement learning for Atari.

EVaDE : Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning Importance of using appropriate baselines for evaluation of data-efficiency in deep reinforcement learning for Atari

Reference 19

Resolution: verified exact; local_arxiv, observed 2026-08-10T19:55:36.152066Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 91ec0fbb-8a00-467d-ab43-64022287304d · outbound

This paper cites V ariational Dropout and the Local Reparameterization Trick.

EVaDE : Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning V ariational Dropout and the Local Reparameterization Trick

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:55:36.390199Z

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Observation c4ddc1dc-9f5b-4b34-a035-9d63e5d7c0ab · outbound

This paper cites CURL: Contrastive Unsupervised Representations for Reinforcement Learn- ing.

EVaDE : Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning CURL: Contrastive Unsupervised Representations for Reinforcement Learn- ing

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:55:36.379986Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 5136596c-1042-4109-9d92-e51fda210235 · outbound

This paper cites Guided Policy Search.

EVaDE : Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning Guided Policy Search

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:55:36.369429Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 74e99bcc-5da9-4560-9591-fb50c9421966 · outbound

This paper cites Neural Network Dynamics for Model-Based Deep Reinforcement Learning with Model-Free Fine-Tuning.

EVaDE : Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning Neural Network Dynamics for Model-Based Deep Reinforcement Learning with Model-Free Fine-Tuning

Reference 23

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Observation 86bcb8c5-7652-4c65-8e2d-606352d0bbe6 · outbound

This paper cites Action-Conditional Video Prediction Using Deep Networks in Atari Games.

EVaDE : Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning Action-Conditional Video Prediction Using Deep Networks in Atari Games

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:55:36.358730Z

Source-reported events for the cited work

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Observation 579b6bf4-56eb-4925-a5a5-02fb1a54a727 · outbound

This paper cites Bootstrapped Thompson Sampling and Deep Exploration.

EVaDE : Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning Bootstrapped Thompson Sampling and Deep Exploration

Reference 25

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Observation 31acf276-8501-47d5-9c22-f2131e982511 · outbound

This paper cites Why is Posterior Sampling Better than Optimism for Reinforcement Learning? InInternational Conference on Machine Learning , pages 2701–2710, 2017.

EVaDE : Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning Why is Posterior Sampling Better than Optimism for Reinforcement Learning? InInternational Conference on Machine Learning , pages 2701–2710, 2017

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:55:36.347825Z

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Observation eb08a996-4601-4d49-8cee-e48b2dbc7df9 · outbound

This paper cites (More) Efficient Reinforcement Learning via Posterior Sampling.

EVaDE : Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning (More) Efficient Reinforcement Learning via Posterior Sampling

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:55:36.337350Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a0d82c19-06b1-48e2-9b55-7a81a83a47d3 · outbound

This paper cites Deep Exploration via Bootstrapped DQN.

EVaDE : Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning Deep Exploration via Bootstrapped DQN

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:55:36.325606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c3e4286c-2b98-4250-8750-e9eb24558df7 · outbound

This paper cites Generalization and Exploration via Randomized Value Functions.

EVaDE : Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning Generalization and Exploration via Randomized Value Functions

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:55:36.314672Z

Source-reported events for the cited work

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Observation 47196a34-5709-4e9d-a51d-ca9638fee0d9 · outbound

This paper cites Chen, Xi Chen, T amim Asfour, Pieter Abbeel, and Marcin Andrychowicz.

EVaDE : Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning Chen, Xi Chen, T amim Asfour, Pieter Abbeel, and Marcin Andrychowicz

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:55:36.304401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 53751a90-4749-456a-b8e4-023df994e106 · outbound

This paper cites Evolution Strategies as a Scalable Alternative to Reinforcement Learning.

EVaDE : Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning Evolution Strategies as a Scalable Alternative to Reinforcement Learning

Reference 31

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Observation 3545d01f-97b2-4f5d-bb40-dede0c232f49 · outbound

This paper cites Proximal Policy Optimization Algorithms.

EVaDE : Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning Proximal Policy Optimization Algorithms

Reference 32

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Observation d9babd3d-aebf-46ab-a1fc-02767ec75d8d · outbound

This paper cites Dropout: A Simple Way to Prevent Neural Networks from Overfitting.

EVaDE : Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning Dropout: A Simple Way to Prevent Neural Networks from Overfitting

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:55:36.294003Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9b392dea-4d86-489c-961f-efe6e4b9c42a · outbound

This paper cites A Bayesian Framework for Reinforcement Learning.

EVaDE : Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning A Bayesian Framework for Reinforcement Learning

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:55:36.283081Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3337524b-074e-4167-8d95-62f811177037 · outbound

This paper cites Dyna, an Integrated Architecture for Learning, Planning, and Reacting.

EVaDE : Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning Dyna, an Integrated Architecture for Learning, Planning, and Reacting

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:55:36.272519Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ae7ca540-fa42-4f2f-bfd0-c3103dd045a2 · outbound

This paper cites On the Likelihood that One Unknown Probability Exceeds Another in View of the Evidence of Two Samples.

EVaDE : Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning On the Likelihood that One Unknown Probability Exceeds Another in View of the Evidence of Two Samples

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:55:36.261017Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 56971bb4-63ac-4527-936c-659ef8843b13 · outbound

This paper cites V ariational Inference for the Multi-Armed Contextual Bandit.

EVaDE : Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning V ariational Inference for the Multi-Armed Contextual Bandit

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:55:36.249645Z

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Observation 04096cd6-3bb0-49d8-aa3c-df0d15ccae3d · outbound

This paper cites When to Use Parametric Models in Reinforcement Learning? In NeurIPS, pages 14322–14333, 2019.

EVaDE : Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning When to Use Parametric Models in Reinforcement Learning? In NeurIPS, pages 14322–14333, 2019

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:55:36.238370Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ef06e995-8512-4a23-97c7-88d960590991 · outbound

This paper cites Tensor2Tensor for Neural Machine Translation.

EVaDE : Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning Tensor2Tensor for Neural Machine Translation

Reference 39

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Source-reported events for the cited work

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Observation d32c3623-7c1c-4c12-a132-85d260f028ba · outbound

This paper cites Thompson Sampling via Local Uncertainty.

EVaDE : Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning Thompson Sampling via Local Uncertainty

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:55:36.225374Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f8dbd2ca-f4a8-4222-bcaa-8bfaf5e3e24d · outbound

This paper cites Model Predictive Path Integral Control using Covariance Variable Importance Sampling.

EVaDE : Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning Model Predictive Path Integral Control using Covariance Variable Importance Sampling

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-10T19:55:36.038638Z

Source-reported events for the cited work

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Observation 9c55c9e9-4909-43ce-a579-781add8af480 · outbound

This paper cites NADPEx: An On-Policy Temporally Consistent Exploration Method for Deep Reinforcement Learning.

EVaDE : Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning NADPEx: An On-Policy Temporally Consistent Exploration Method for Deep Reinforcement Learning

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:55:36.213655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7c5363cd-cfff-472a-8eb2-8dfa889e9bfc · outbound

This paper cites Mastering atari games with limited data.

EVaDE : Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning Mastering atari games with limited data

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:55:36.201905Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 70a78d5d-c334-49f4-8b05-24380d0cd583 · outbound

This paper cites Scalable Thompson Sampling via Optimal Transport.

EVaDE : Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning Scalable Thompson Sampling via Optimal Transport

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:55:36.188610Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b9521dd6-d9a3-4c31-9192-6441e53a3706 · outbound

This paper cites Model Based Reinforcement Learning for Atari.

EVaDE : Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning Model Based Reinforcement Learning for Atari

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T19:55:36.176782Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 0ee6a3ed-584e-472c-80d0-afbc07236faa · outbound

This paper cites Prioritized Sequence Experience Replay.

EVaDE : Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning Prioritized Sequence Experience Replay

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-10T19:55:35.912989Z

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Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.