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Paper Citation Record · LEDGER

Quantitative Particle Approximation for Controlled Nonlinear Filtering

As of 10 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2608.00686.

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pith.paper-citation-record.v1
2608.00686 v1

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measured 35 of 35 reference resolution

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35 of 35 outbound references displayed

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Outbound references

Observation 825ee661-b7c5-47ba-a4cc-f65772d26f71 · outbound

This paper cites Backward SDEs for optimal control of partially observed path-dependent stochastic systems: A control randomization approach.The Annals of Applied Probability, 28(3):1634–1678, 2018.

Quantitative Particle Approximation for Controlled Nonlinear Filtering Backward SDEs for optimal control of partially observed path-dependent stochastic systems: A control randomization approach.The Annals of Applied Probability, 28(3):1634–1678, 2018

Reference 1

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Observation ad4dbda3-d524-4bf8-ad94-3df2f91ccbb4 · outbound

This paper cites Randomized filtering and Bellman equa- tion in Wasserstein space for partial observation control problem.Stochastic Processes and their Applications, 129(2):674–711, 2019.

Quantitative Particle Approximation for Controlled Nonlinear Filtering Randomized filtering and Bellman equa- tion in Wasserstein space for partial observation control problem.Stochastic Processes and their Applications, 129(2):674–711, 2019

Reference 2

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Observation 356808dc-d5e6-4650-b04d-fddeef999b6e · outbound

This paper cites Mean field control and finite agent approxi- mation for regime-switching jump diffusions.Applied Mathematics & Optimization, 88(2):36, 2023.

Quantitative Particle Approximation for Controlled Nonlinear Filtering Mean field control and finite agent approxi- mation for regime-switching jump diffusions.Applied Mathematics & Optimization, 88(2):36, 2023

Reference 3

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This paper cites an unresolved cited work.

Quantitative Particle Approximation for Controlled Nonlinear Filtering Unresolved cited work

Reference 4

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Observation edd65eaf-9d09-4c65-b044-3465ca03d6f1 · outbound

This paper cites Comparison for semi-continuous viscosity solutions for second order pdes on the Wasserstein space.Journal of Differential Equations, 455:113963, 2026.

Quantitative Particle Approximation for Controlled Nonlinear Filtering Comparison for semi-continuous viscosity solutions for second order pdes on the Wasserstein space.Journal of Differential Equations, 455:113963, 2026

Reference 5

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Observation 95366279-1b6f-4b59-a619-ccc893a2076e · outbound

This paper cites A comparison principle for Wasserstein PDEs with state- and law-dependent common noise.

Quantitative Particle Approximation for Controlled Nonlinear Filtering A comparison principle for Wasserstein PDEs with state- and law-dependent common noise

Reference 6

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Observation 379d7da5-a2cc-4ba3-a28c-77c5388ccce8 · outbound

This paper cites Comparison of viscosity solutions for a class of second- order pdes on the Wasserstein space.Communications in Partial Differential Equations, 50(4):570–613, 2025.

Quantitative Particle Approximation for Controlled Nonlinear Filtering Comparison of viscosity solutions for a class of second- order pdes on the Wasserstein space.Communications in Partial Differential Equations, 50(4):570–613, 2025

Reference 7

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Observation 72c2ccc7-10a7-45b6-88a6-533c194bd6ec · outbound

This paper cites Convergence rate of particle system for second-order pdes on Wasserstein space.SIAM Journal on Control and Optimization, 63(3):1768–1782, 2025.

Quantitative Particle Approximation for Controlled Nonlinear Filtering Convergence rate of particle system for second-order pdes on Wasserstein space.SIAM Journal on Control and Optimization, 63(3):1768–1782, 2025

Reference 8

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Observation 1821006b-680e-42ba-a8e0-96a90ef81620 · outbound

This paper cites Cambridge University Press, Cam- bridge, 1992.

Quantitative Particle Approximation for Controlled Nonlinear Filtering Cambridge University Press, Cam- bridge, 1992

Reference 9

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Observation dc1bba98-14a8-4483-bea5-c3ae74719d5d · outbound

This paper cites Limit theory for mean-field control problems with common noise adapted controls.arXiv preprint arXiv:2509.14734, 2025.

Quantitative Particle Approximation for Controlled Nonlinear Filtering Limit theory for mean-field control problems with common noise adapted controls.arXiv preprint arXiv:2509.14734, 2025

Reference 10

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Observation 92d94a5d-9822-4b77-9477-62d6492d93aa · outbound

This paper cites Max Reppen, and H.

Quantitative Particle Approximation for Controlled Nonlinear Filtering Max Reppen, and H

Reference 11

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Observation 793cd016-3919-4041-a734-f4df3711342f · outbound

This paper cites Souganidis.

Quantitative Particle Approximation for Controlled Nonlinear Filtering Souganidis

Reference 12

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Observation 5615dbe3-c5e5-4bd0-96df-6c403e07acc9 · outbound

This paper cites Sharp convergence rates for mean field control in the region of strong regularity.

Quantitative Particle Approximation for Controlled Nonlinear Filtering Sharp convergence rates for mean field control in the region of strong regularity

Reference 13

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Observation 18a3eb82-5daa-4814-abe9-38cfb7120b3e · outbound

This paper cites Souganidis.

Quantitative Particle Approximation for Controlled Nonlinear Filtering Souganidis

Reference 14

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Observation f5292ed4-2a4b-4ee6-b989-ccc367b3dc47 · outbound

This paper cites A survey of convergence results on particle filtering methods for practition- ers.IEEE Transactions on Signal Processing, 50(3):736–746, 2002.

Quantitative Particle Approximation for Controlled Nonlinear Filtering A survey of convergence results on particle filtering methods for practition- ers.IEEE Transactions on Signal Processing, 50(3):736–746, 2002

Reference 15

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Quantitative Particle Approximation for Controlled Nonlinear Filtering Unresolved cited work

Reference 16

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Observation 32974f24-b86e-4c3b-bc86-56714a34c88f · outbound

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Quantitative Particle Approximation for Controlled Nonlinear Filtering Unresolved cited work

Reference 17

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Quantitative Particle Approximation for Controlled Nonlinear Filtering Unresolved cited work

Reference 18

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Observation a32d488b-932c-4a77-9e55-f5983709c73e · outbound

This paper cites On the optimal rate for the convergence problem in mean field control.Journal of Functional Analysis, 287(12), 2024.

Quantitative Particle Approximation for Controlled Nonlinear Filtering On the optimal rate for the convergence problem in mean field control.Journal of Functional Analysis, 287(12), 2024

Reference 19

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This paper cites Well-posedness of Hamilton–Jacobi equations in the Wasserstein space: non-convex hamiltonians and common noise.Communications in Partial Differential Equations, 50(1–2):1–52, 2025.

Quantitative Particle Approximation for Controlled Nonlinear Filtering Well-posedness of Hamilton–Jacobi equations in the Wasserstein space: non-convex hamiltonians and common noise.Communications in Partial Differential Equations, 50(1–2):1–52, 2025

Reference 20

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Observation 696bb0c2-0ea0-46d0-9ad8-8865b5da52b3 · outbound

This paper cites Probability and Its Applications.

Quantitative Particle Approximation for Controlled Nonlinear Filtering Probability and Its Applications

Reference 21

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Observation 6f0a8948-148c-445f-bfeb-f10e2e9da50b · outbound

This paper cites McKean–Vlasov optimal control: limit theory and equivalence between different formulations.Mathematics of Operations Research, 47(4):2891–2930, 2022.

Quantitative Particle Approximation for Controlled Nonlinear Filtering McKean–Vlasov optimal control: limit theory and equivalence between different formulations.Mathematics of Operations Research, 47(4):2891–2930, 2022

Reference 22

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Observation 8071a9e4-5d55-44d0-bdee-1fc4eac36bc6 · outbound

This paper cites McKean–Vlasov optimal control: the dynamic pro- gramming principle.The Annals of Probability, 50(2):791–833, 2022.

Quantitative Particle Approximation for Controlled Nonlinear Filtering McKean–Vlasov optimal control: the dynamic pro- gramming principle.The Annals of Probability, 50(2):791–833, 2022

Reference 23

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Observation 80da288d-a9bb-4fd8-a739-95b41d680743 · outbound

This paper cites Springer, New York, 2001.

Quantitative Particle Approximation for Controlled Nonlinear Filtering Springer, New York, 2001

Reference 24

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Observation 89266b0e-40a6-4e78-aeeb-a6c011f86829 · outbound

This paper cites On the rate of convergence in Wasserstein distance of the empirical measure.Probability Theory and Related Fields, 162(3):707–738, 2015.

Quantitative Particle Approximation for Controlled Nonlinear Filtering On the rate of convergence in Wasserstein distance of the empirical measure.Probability Theory and Related Fields, 162(3):707–738, 2015

Reference 25

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Observation 847837bc-0c54-493c-9f75-0a70c4a7149f · outbound

This paper cites Prentice-Hall, Englewood Cliffs, NJ, 1964.

Quantitative Particle Approximation for Controlled Nonlinear Filtering Prentice-Hall, Englewood Cliffs, NJ, 1964

Reference 26

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Observation 1ae637a3-8697-4596-aa60-3ec646707457 · outbound

This paper cites Finite dimensional approximations of Hamilton– Jacobi–Bellman equations in spaces of probability measures.SIAM Journal on Mathematical Analysis, 53(2):1320–1356, 2021.

Quantitative Particle Approximation for Controlled Nonlinear Filtering Finite dimensional approximations of Hamilton– Jacobi–Bellman equations in spaces of probability measures.SIAM Journal on Mathematical Analysis, 53(2):1320–1356, 2021

Reference 27

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Observation bdf59656-7cbb-4524-93b4-813d976d510a · outbound

This paper cites Rate of convergence for particle approximation of pdes in Wasserstein space.Journal of Applied Probability, 59(4):992–1008, 2022.

Quantitative Particle Approximation for Controlled Nonlinear Filtering Rate of convergence for particle approximation of pdes in Wasserstein space.Journal of Applied Probability, 59(4):992–1008, 2022

Reference 28

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Observation 5a61f69d-a17a-4089-bd53-20dcc5fb2f03 · outbound

This paper cites Gordon, David J.

Quantitative Particle Approximation for Controlled Nonlinear Filtering Gordon, David J

Reference 29

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Observation b43ef2dc-e5ee-44c6-a65f-8cadc0b03409 · outbound

This paper cites Monte carlo filter and smoother for non-Gaussian nonlinear state space models.Journal of Computational and Graphical Statistics, 5(1):1–25, 1996.

Quantitative Particle Approximation for Controlled Nonlinear Filtering Monte carlo filter and smoother for non-Gaussian nonlinear state space models.Journal of Computational and Graphical Statistics, 5(1):1–25, 1996

Reference 30

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Observation a8299a48-7dfc-464b-bb97-226e10f5015a · outbound

This paper cites Limit theory for controlled McKean–Vlasov dynamics.SIAM Journal on Control and Opti- mization, 55(3):1641–1672, 2017.

Quantitative Particle Approximation for Controlled Nonlinear Filtering Limit theory for controlled McKean–Vlasov dynamics.SIAM Journal on Control and Opti- mization, 55(3):1641–1672, 2017

Reference 31

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Observation b2a1ff8a-a40b-4c65-a9c4-165e41278a54 · outbound

This paper cites an unresolved cited work.

Quantitative Particle Approximation for Controlled Nonlinear Filtering Unresolved cited work

Reference 32

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T00:41:46.312004Z digest=sha256:5107b6798d69fb6fe3c8edf422caf8ecb7957158b26b496986f35eab50736f60

Observation 2ead31ff-f025-48e4-a598-3b78c0ac078f · outbound

This paper cites Dynamic programming for optimal control of stochastic McKean–Vlasov dynamics.SIAM Journal on Control and Optimization, 55(2):1069–1101, 2017.

Quantitative Particle Approximation for Controlled Nonlinear Filtering Dynamic programming for optimal control of stochastic McKean–Vlasov dynamics.SIAM Journal on Control and Optimization, 55(2):1069–1101, 2017

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T00:41:47.239464Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T00:41:46.392493Z digest=sha256:3876e85e6ccb98603d74930bbb95b80ca8e1609c32af928f02e8f858026a2dae

Observation 9d2672e6-3f1c-4f3b-a5ab-a2a7d8bddf3b · outbound

This paper cites Mete Soner and Qinxin Yan.

Quantitative Particle Approximation for Controlled Nonlinear Filtering Mete Soner and Qinxin Yan

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-05T00:41:46.493334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T00:41:46.493334Z digest=sha256:93d49359ef9ab98d8f897877451abf6cbdad3b6b3436a59d1eda27885cd58283

Observation 1013a1ce-73f7-4481-9d57-a1a4efc15fa6 · outbound

This paper cites Topics in propagation of chaos.

Quantitative Particle Approximation for Controlled Nonlinear Filtering Topics in propagation of chaos

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T00:41:46.995274Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-05T00:41:46.559594Z digest=sha256:10e306d991fa0e84b75a1fd25242d4f00a8e5003543f20351d00b61f3608a9e7

Pith citing papers

No inbound Pith citation observations are available.