Paper Citation Record · LEDGER

State-Dependent Observation Noise Reintroduces Epistemic Value in Linear-Gaussian Active Inference

As of 9 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2607.20306.

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

pith.paper-citation-record.v1
2607.20306 v1

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T10:17:21.826239Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

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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

38 of 38 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6712e6fd-e8eb-4a6e-8402-6cefe29c813a · outbound

This paper cites On epistemics in expected free energy for linear Gaussian state space models.

State-Dependent Observation Noise Reintroduces Epistemic Value in Linear-Gaussian Active Inference On epistemics in expected free energy for linear Gaussian state space models

Reference 1

Resolution: verified exact; doi, observed 2026-08-01T10:18:24.499620Z

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Observation b5f85af1-1d4f-4199-b6a1-6af928f44051 · outbound

This paper cites Realising Synthetic Active Inference Agents, Part I: Epistemic Objectives and Graphical Specification Language.

State-Dependent Observation Noise Reintroduces Epistemic Value in Linear-Gaussian Active Inference Realising Synthetic Active Inference Agents, Part I: Epistemic Objectives and Graphical Specification Language

Reference 2

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Observation 37ab3f8e-ee2f-4786-be12-a4b6a43be42b · outbound

This paper cites Realizing synthetic active inference agents, Part II: Variational message updates.

State-Dependent Observation Noise Reintroduces Epistemic Value in Linear-Gaussian Active Inference Realizing synthetic active inference agents, Part II: Variational message updates

Reference 3

Resolution: verified exact; doi, observed 2026-08-01T10:18:24.286946Z

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Observation 9ecdef95-7121-48ea-9ef8-f83f03e7c2e8 · outbound

This paper cites Dual effect, certainty equivalence, and separation in stochastic control.

State-Dependent Observation Noise Reintroduces Epistemic Value in Linear-Gaussian Active Inference Dual effect, certainty equivalence, and separation in stochastic control

Reference 4

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Observation 8e8027ae-b041-419e-9b09-464bd6d0aa45 · outbound

This paper cites Nonlinear estimation with state-dependent Gaussian observation noise.

State-Dependent Observation Noise Reintroduces Epistemic Value in Linear-Gaussian Active Inference Nonlinear estimation with state-dependent Gaussian observation noise

Reference 5

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Observation 7504acf8-e5f2-4bde-ad91-27628371bc32 · outbound

This paper cites Dual control theory.

State-Dependent Observation Noise Reintroduces Epistemic Value in Linear-Gaussian Active Inference Dual control theory

Reference 6

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Observation 7b33532d-0d50-4aaa-b109-18edee7044fa · outbound

This paper cites Dual control theory problems.

State-Dependent Observation Noise Reintroduces Epistemic Value in Linear-Gaussian Active Inference Dual control theory problems

Reference 7

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Observation 72a60d20-ce7d-438c-b500-9c12d9dac781 · outbound

This paper cites Active inference on discrete state- spaces: A synthesis.

State-Dependent Observation Noise Reintroduces Epistemic Value in Linear-Gaussian Active Inference Active inference on discrete state- spaces: A synthesis

Reference 8

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Observation 45a56a2d-d083-4533-b9b2-1a9de37590ad · outbound

This paper cites Whence the expected free energy? Neural Comput.

State-Dependent Observation Noise Reintroduces Epistemic Value in Linear-Gaussian Active Inference Whence the expected free energy? Neural Comput

Reference 9

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Observation c93f7a19-4e4c-42f9-8dd9-e57db4f3b431 · outbound

This paper cites Active inference and epistemic value in graphical models.

State-Dependent Observation Noise Reintroduces Epistemic Value in Linear-Gaussian Active Inference Active inference and epistemic value in graphical models

Reference 10

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Observation c1def933-5f1e-4474-91d2-5f68bf4c56a3 · outbound

This paper cites Dual effect, certainty equivalence, and separation revisited: A counterexample and a relaxed characterization for optimality.

State-Dependent Observation Noise Reintroduces Epistemic Value in Linear-Gaussian Active Inference Dual effect, certainty equivalence, and separation revisited: A counterexample and a relaxed characterization for optimality

Reference 11

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Observation c1f4581c-3a48-4924-acf7-371a341b1962 · outbound

This paper cites A counterexample in stochastic optimum control.

State-Dependent Observation Noise Reintroduces Epistemic Value in Linear-Gaussian Active Inference A counterexample in stochastic optimum control

Reference 12

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Observation 5b0c7d8e-8f7b-43d4-b33d-047f181da32c · outbound

This paper cites A generalization of the Kalman filter for models with state-dependent observation variance.

State-Dependent Observation Noise Reintroduces Epistemic Value in Linear-Gaussian Active Inference A generalization of the Kalman filter for models with state-dependent observation variance

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-01T10:17:19.811643Z

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Observation 112dc75d-4254-4672-96bf-9e96a4e199e0 · outbound

This paper cites Alignment of irregular grains by radiative torques: efficiency study.

State-Dependent Observation Noise Reintroduces Epistemic Value in Linear-Gaussian Active Inference Alignment of irregular grains by radiative torques: efficiency study

Reference 14

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Observation ea59a2c9-2ca5-4db1-ad7d-aa6d46b38fc3 · outbound

This paper cites Revisiting active perception.

State-Dependent Observation Noise Reintroduces Epistemic Value in Linear-Gaussian Active Inference Revisiting active perception

Reference 15

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Observation cdfbce26-1a7f-4d8a-9835-17370b6a2755 · outbound

This paper cites The belief roadmap: Efficient planning in belief space by factoring the covariance.

State-Dependent Observation Noise Reintroduces Epistemic Value in Linear-Gaussian Active Inference The belief roadmap: Efficient planning in belief space by factoring the covariance

Reference 16

Resolution: verified exact; doi, observed 2026-08-01T10:18:23.863060Z

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Observation b0779535-af21-4c36-a023-7b096f9d4823 · outbound

This paper cites Belief space planning assuming maximum likelihood observations.

State-Dependent Observation Noise Reintroduces Epistemic Value in Linear-Gaussian Active Inference Belief space planning assuming maximum likelihood observations

Reference 17

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Observation 419c59f3-9d68-43ce-8e20-77d1f4124bda · outbound

This paper cites Motion planning under uncertainty using iterative local optimization in belief space.

State-Dependent Observation Noise Reintroduces Epistemic Value in Linear-Gaussian Active Inference Motion planning under uncertainty using iterative local optimization in belief space

Reference 18

Resolution: verified exact; doi, observed 2026-08-01T10:18:23.699109Z

Source-reported events for the cited work

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Observation f30b801a-2a46-47de-b913-15398cbfa18b · outbound

This paper cites Randomized compiling for scalable quantum computing on a noisy superconducting quantum processor.

State-Dependent Observation Noise Reintroduces Epistemic Value in Linear-Gaussian Active Inference Randomized compiling for scalable quantum computing on a noisy superconducting quantum processor

Reference 19

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Observation 93febb44-4762-4c76-8af0-1cb42f24a72c · outbound

This paper cites Plane-Wave Ultrasound Beamforming Through Independent Component Analysis.

State-Dependent Observation Noise Reintroduces Epistemic Value in Linear-Gaussian Active Inference Plane-Wave Ultrasound Beamforming Through Independent Component Analysis

Reference 20

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Observation fcb21686-5de0-4dba-8b3c-db53e06e2c28 · outbound

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State-Dependent Observation Noise Reintroduces Epistemic Value in Linear-Gaussian Active Inference Working memory, attention, and salience in active inference

Reference 21

Resolution: verified exact; doi, observed 2026-08-01T10:18:23.543287Z

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Observation f2c7dafd-63e6-47ef-b297-ed4d8f03efdb · outbound

This paper cites Introducing a Bayesian model of selective attention based on active inference.

State-Dependent Observation Noise Reintroduces Epistemic Value in Linear-Gaussian Active Inference Introducing a Bayesian model of selective attention based on active inference

Reference 22

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Observation 84b8003f-7f45-45ac-8241-84b34fbea90f · outbound

This paper cites Codes on graphs: Normal realizations.

State-Dependent Observation Noise Reintroduces Epistemic Value in Linear-Gaussian Active Inference Codes on graphs: Normal realizations

Reference 23

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Observation 7c4417b1-178b-48a7-ab74-022da1d3e540 · outbound

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State-Dependent Observation Noise Reintroduces Epistemic Value in Linear-Gaussian Active Inference Factor graphs and the sum-product algorithm

Reference 24

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Observation 7a4c15b6-e92d-403d-82e7-75cb56233afe · outbound

This paper cites Biomechanical surrogate modelling using stabilized vectorial greedy kernel methods.

State-Dependent Observation Noise Reintroduces Epistemic Value in Linear-Gaussian Active Inference Biomechanical surrogate modelling using stabilized vectorial greedy kernel methods

Reference 25

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Observation 31dc8083-8f8e-4983-a2b3-1ba9275330a0 · outbound

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State-Dependent Observation Noise Reintroduces Epistemic Value in Linear-Gaussian Active Inference The factor graph approach to model-based signal processing

Reference 26

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Observation cd28a293-91d6-42ce-896f-8a873614ea7d · outbound

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State-Dependent Observation Noise Reintroduces Epistemic Value in Linear-Gaussian Active Inference Simulating active inference processes by message passing

Reference 27

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Observation 04ac2a01-5995-4e34-9b9e-45416912ffe9 · outbound

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State-Dependent Observation Noise Reintroduces Epistemic Value in Linear-Gaussian Active Inference Variational message passing and local constraint manipulation in factor graphs

Reference 28

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Observation cfd065d5-da62-45c0-8ead-6e7d89b747e6 · outbound

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State-Dependent Observation Noise Reintroduces Epistemic Value in Linear-Gaussian Active Inference RxInfer: A Julia package for reactive real-time Bayesian inference

Reference 29

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Observation eb796b2b-ae94-464d-ac2c-9368152d8757 · outbound

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State-Dependent Observation Noise Reintroduces Epistemic Value in Linear-Gaussian Active Inference Generalised filtering

Reference 30

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Source-reported events for the cited work

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Observation 128d5f1f-31ed-4820-b62a-bc0053ca77db · outbound

This paper cites Kalman filters as the steady-state solution of gradient descent on variational free energy.

State-Dependent Observation Noise Reintroduces Epistemic Value in Linear-Gaussian Active Inference Kalman filters as the steady-state solution of gradient descent on variational free energy

Reference 31

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Observation 291c0b83-87ae-42fd-a2c6-0a7b0b1b0dab · outbound

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State-Dependent Observation Noise Reintroduces Epistemic Value in Linear-Gaussian Active Inference Optimal Filtering; Prentice-Hall: Englewood Cliffs, NJ, USA, 1979

Reference 32

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Observation 0d2179ac-3c1b-4f86-8e3c-51eb01f19b46 · outbound

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State-Dependent Observation Noise Reintroduces Epistemic Value in Linear-Gaussian Active Inference Linear Estimation; Prentice-Hall: Upper Saddle River, NJ, USA, 2000

Reference 33

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Observation 1f6c24e2-96a1-4a95-ab59-9c4964b3899b · outbound

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State-Dependent Observation Noise Reintroduces Epistemic Value in Linear-Gaussian Active Inference Bayesian Filtering and Smoothing, 2nd ed.; Cambridge University Press: Cambridge, UK, 2023

Reference 34

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Observation ad8851f5-8700-44b7-b1fa-1c858e110766 · outbound

This paper cites cpomdp, version 0.4.2; Zenodo, 2026.

State-Dependent Observation Noise Reintroduces Epistemic Value in Linear-Gaussian Active Inference cpomdp, version 0.4.2; Zenodo, 2026

Reference 35

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Observation 33e25840-9478-4ff8-96d1-487e98909c32 · outbound

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State-Dependent Observation Noise Reintroduces Epistemic Value in Linear-Gaussian Active Inference pymdp: A Python library for active inference in discrete state spaces

Reference 36

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Observation ca966765-a3bd-4325-93f5-a876acff89f0 · outbound

This paper cites Active inference and epistemic value.

State-Dependent Observation Noise Reintroduces Epistemic Value in Linear-Gaussian Active Inference Active inference and epistemic value

Reference 37

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Observation caf4ec98-3403-45b9-ad6f-3a1d9219a62a · outbound

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State-Dependent Observation Noise Reintroduces Epistemic Value in Linear-Gaussian Active Inference Unresolved cited work

Reference 147

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Pith citing papers

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