Paper Citation Record · LEDGER

Deep Generative Model-Aided Power System Dynamic State Estimation and Reconstruction with Unknown Control Inputs or Data Distributions

As of 14 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2501.02928.

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

pith.paper-citation-record.v1
2501.02928 v1

Coverage vector

measured 31 of 31 reference resolution

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One-hop event checks from named stored sources.

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Pith citing papers itemized under the disclosed page cap.

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Source: cited_works

Reference resolution

31 of 31 outbound references displayed

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External citation measurements

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Outbound references

Observation 0af6e963-9bc0-4539-9541-4e58f72b9c09 · outbound

This paper cites Roles of dynamic state estimation in power system modeling, monitoring and operation,.

Deep Generative Model-Aided Power System Dynamic State Estimation and Reconstruction with Unknown Control Inputs or Data Distributions Roles of dynamic state estimation in power system modeling, monitoring and operation,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:06:16.276759Z

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Observation b2b60a1d-820f-423c-945c-fb2cef9c9334 · outbound

This paper cites Dynamic state estimation for power system control and protection,.

Deep Generative Model-Aided Power System Dynamic State Estimation and Reconstruction with Unknown Control Inputs or Data Distributions Dynamic state estimation for power system control and protection,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:06:16.261974Z

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Observation 0a1b6134-e04a-4ac8-b7d1-41c02d9b42a9 · outbound

This paper cites Power system dynamic state estimation: Motivations, definitions, methodologies, and future work,.

Deep Generative Model-Aided Power System Dynamic State Estimation and Reconstruction with Unknown Control Inputs or Data Distributions Power system dynamic state estimation: Motivations, definitions, methodologies, and future work,

Reference 3

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Observation 6633c146-7d1f-4d74-959c-fa18cc3b7db4 · outbound

This paper cites Dynamic state estimation in power system by applying the extended kalman filter with unknown inputs to phasor measurements,.

Deep Generative Model-Aided Power System Dynamic State Estimation and Reconstruction with Unknown Control Inputs or Data Distributions Dynamic state estimation in power system by applying the extended kalman filter with unknown inputs to phasor measurements,

Reference 4

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Observation 2fa88a49-3bfb-4abd-9429-1987d47e021c · outbound

This paper cites Dynamic state estimation for multi-machine power system by unscented kalman filter with enhanced numerical stability,.

Deep Generative Model-Aided Power System Dynamic State Estimation and Reconstruction with Unknown Control Inputs or Data Distributions Dynamic state estimation for multi-machine power system by unscented kalman filter with enhanced numerical stability,

Reference 5

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Observation 2e48b6b3-2804-43d3-b109-80ea12da5739 · outbound

This paper cites Robust particle filter design with an application to power system state estimation,.

Deep Generative Model-Aided Power System Dynamic State Estimation and Reconstruction with Unknown Control Inputs or Data Distributions Robust particle filter design with an application to power system state estimation,

Reference 6

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Observation b9d6b2c3-9c57-4126-8405-047807082ad0 · outbound

This paper cites Robust unscented kalman filter for power system dynamic state estimation with unknown noise statistics,.

Deep Generative Model-Aided Power System Dynamic State Estimation and Reconstruction with Unknown Control Inputs or Data Distributions Robust unscented kalman filter for power system dynamic state estimation with unknown noise statistics,

Reference 7

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Observation f4269607-7d18-4d46-a033-524633397794 · outbound

This paper cites Precise recovery of corrupted synchrophasors based on autoregressive bayesian low-rank factorization and adaptive k-medoids clustering,.

Deep Generative Model-Aided Power System Dynamic State Estimation and Reconstruction with Unknown Control Inputs or Data Distributions Precise recovery of corrupted synchrophasors based on autoregressive bayesian low-rank factorization and adaptive k-medoids clustering,

Reference 8

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Observation e69850b0-cc09-4d9d-b25c-5e27b6994df4 · outbound

This paper cites A constrained optimization approach to dynamic state estimation for power systems including pmu and missing measurements,.

Deep Generative Model-Aided Power System Dynamic State Estimation and Reconstruction with Unknown Control Inputs or Data Distributions A constrained optimization approach to dynamic state estimation for power systems including pmu and missing measurements,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:06:16.163957Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 5d73a5be-1008-4f98-9d2e-e0d500880d06 · outbound

This paper cites A robust iterated extended kalman filter for power system dynamic state estimation,.

Deep Generative Model-Aided Power System Dynamic State Estimation and Reconstruction with Unknown Control Inputs or Data Distributions A robust iterated extended kalman filter for power system dynamic state estimation,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:06:16.149549Z

Source-reported events for the cited work

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Observation 7fae605f-d71c-4306-baad-bfb41d608b49 · outbound

This paper cites Constrained robust unscented kalman filter for generalized dynamic state estimation,.

Deep Generative Model-Aided Power System Dynamic State Estimation and Reconstruction with Unknown Control Inputs or Data Distributions Constrained robust unscented kalman filter for generalized dynamic state estimation,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:06:16.134653Z

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Observation 7d22b62f-ed0c-41d4-9f2b-909ac7343c47 · outbound

This paper cites A robust data-driven koopman kalman filter for power systems dynamic state estimation,.

Deep Generative Model-Aided Power System Dynamic State Estimation and Reconstruction with Unknown Control Inputs or Data Distributions A robust data-driven koopman kalman filter for power systems dynamic state estimation,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:06:16.119697Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation ede2f6de-9db2-41c4-ae47-743531247616 · outbound

This paper cites Risk mitigation for dynamic state estimation against cyber attacks and unknown inputs,.

Deep Generative Model-Aided Power System Dynamic State Estimation and Reconstruction with Unknown Control Inputs or Data Distributions Risk mitigation for dynamic state estimation against cyber attacks and unknown inputs,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:06:16.104518Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation f913e564-281e-4582-86bd-6388b368ff26 · outbound

This paper cites Correlation-aided robust decentralized dynamic state estimation of power systems with unknown control inputs,.

Deep Generative Model-Aided Power System Dynamic State Estimation and Reconstruction with Unknown Control Inputs or Data Distributions Correlation-aided robust decentralized dynamic state estimation of power systems with unknown control inputs,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:06:16.088972Z

Source-reported events for the cited work

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Observation b7dd5308-a588-4bce-b40d-01bf5af2d08a · outbound

This paper cites Event-trigger particle filter for smart grids with limited communication bandwidth infrastructure,.

Deep Generative Model-Aided Power System Dynamic State Estimation and Reconstruction with Unknown Control Inputs or Data Distributions Event-trigger particle filter for smart grids with limited communication bandwidth infrastructure,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:06:16.074076Z

Source-reported events for the cited work

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Observation 8ad78d35-5824-4874-942c-f772a3b0f219 · outbound

This paper cites Event-trigger heterogeneous nonlinear filter for wide-area measurement systems in power grid,.

Deep Generative Model-Aided Power System Dynamic State Estimation and Reconstruction with Unknown Control Inputs or Data Distributions Event-trigger heterogeneous nonlinear filter for wide-area measurement systems in power grid,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:06:16.058568Z

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Observation abdf6008-c6d9-4c9b-a884-beb07196a21f · outbound

This paper cites An unscented particle filtering approach to decentralized dynamic state estimation for dfig wind turbines in multi-area power systems,.

Deep Generative Model-Aided Power System Dynamic State Estimation and Reconstruction with Unknown Control Inputs or Data Distributions An unscented particle filtering approach to decentralized dynamic state estimation for dfig wind turbines in multi-area power systems,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:06:16.043389Z

Source-reported events for the cited work

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Observation ec5b35b3-25f7-43cd-bb09-66035241c59d · outbound

This paper cites Data-driven adaptive unscented kalman filter for time-varying inertia and damping estimation of utility-scale ibrs considering current limiter,.

Deep Generative Model-Aided Power System Dynamic State Estimation and Reconstruction with Unknown Control Inputs or Data Distributions Data-driven adaptive unscented kalman filter for time-varying inertia and damping estimation of utility-scale ibrs considering current limiter,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:06:16.027689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 39de091f-26f1-428c-8616-bcedecbe24a1 · outbound

This paper cites Esti- mation of rotor angles of synchronous machines using artificial neural networks and local pmu-based quantities,.

Deep Generative Model-Aided Power System Dynamic State Estimation and Reconstruction with Unknown Control Inputs or Data Distributions Esti- mation of rotor angles of synchronous machines using artificial neural networks and local pmu-based quantities,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:06:16.011516Z

Source-reported events for the cited work

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Observation 79277107-697a-49d2-9d7e-6d70ff28d016 · outbound

This paper cites Dynamic state estimation for the advanced brake system of electric vehicles by using deep recurrent neural networks,.

Deep Generative Model-Aided Power System Dynamic State Estimation and Reconstruction with Unknown Control Inputs or Data Distributions Dynamic state estimation for the advanced brake system of electric vehicles by using deep recurrent neural networks,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:06:15.994577Z

Source-reported events for the cited work

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Observation 91de7347-1752-4700-8518-6b610f0912a6 · outbound

This paper cites Power plant model parameter calibration using conditional variational autoencoder,.

Deep Generative Model-Aided Power System Dynamic State Estimation and Reconstruction with Unknown Control Inputs or Data Distributions Power plant model parameter calibration using conditional variational autoencoder,

Reference 21

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Observation 1391cf51-46a3-49f1-9d5a-f146d57fae4d · outbound

This paper cites Training a dynamic neural network to detect false data injection attacks under multiple unforeseen operating conditions,.

Deep Generative Model-Aided Power System Dynamic State Estimation and Reconstruction with Unknown Control Inputs or Data Distributions Training a dynamic neural network to detect false data injection attacks under multiple unforeseen operating conditions,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:06:15.964869Z

Source-reported events for the cited work

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Observation f8e99259-230b-4d72-a9f5-ed187b13f494 · outbound

This paper cites Spatio-temporal generative adversarial network based power distribution network state estimation with multiple time-scale measurements,.

Deep Generative Model-Aided Power System Dynamic State Estimation and Reconstruction with Unknown Control Inputs or Data Distributions Spatio-temporal generative adversarial network based power distribution network state estimation with multiple time-scale measurements,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:06:15.949343Z

Source-reported events for the cited work

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Observation a6f43602-385a-49db-9301-1c1e33aedfa2 · outbound

This paper cites Latent Diffusion Model-Enabled Low-Latency Semantic Communication in the Presence of Semantic Ambiguities and Wireless Channel Noises.

Deep Generative Model-Aided Power System Dynamic State Estimation and Reconstruction with Unknown Control Inputs or Data Distributions Latent Diffusion Model-Enabled Low-Latency Semantic Communication in the Presence of Semantic Ambiguities and Wireless Channel Noises

Reference 24

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Source-reported events for the cited work

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Observation c8e82061-69b5-470e-8b42-3d97404350ca · outbound

This paper cites Hybrid LLM-DDQN based Joint Optimization of V2I Communication and Autonomous Driving.

Deep Generative Model-Aided Power System Dynamic State Estimation and Reconstruction with Unknown Control Inputs or Data Distributions Hybrid LLM-DDQN based Joint Optimization of V2I Communication and Autonomous Driving

Reference 25

Resolution: verified exact; local_arxiv, observed 2026-08-10T22:06:15.830262Z

Source-reported events for the cited work

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Observation 580673e1-1b4c-4fa3-a4d3-09a5384b9549 · outbound

This paper cites Robust fast pmu measurement recovery enhanced by randomized singular value and sequential tucker decomposition,.

Deep Generative Model-Aided Power System Dynamic State Estimation and Reconstruction with Unknown Control Inputs or Data Distributions Robust fast pmu measurement recovery enhanced by randomized singular value and sequential tucker decomposition,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:06:15.933815Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation c62b2047-d2f0-4b3a-9da1-55414e8cc3e8 · outbound

This paper cites Hybrid symbolic-numeric framework for power system modeling and analysis,.

Deep Generative Model-Aided Power System Dynamic State Estimation and Reconstruction with Unknown Control Inputs or Data Distributions Hybrid symbolic-numeric framework for power system modeling and analysis,

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-10T22:06:15.769067Z

Source-reported events for the cited work

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Observation d0b2fc4a-a5d2-4493-a290-b80a6e1f5878 · outbound

This paper cites Stability and convergence of a randomized model predictive control strategy,.

Deep Generative Model-Aided Power System Dynamic State Estimation and Reconstruction with Unknown Control Inputs or Data Distributions Stability and convergence of a randomized model predictive control strategy,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:06:15.908810Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation dd711972-5861-43d3-a571-43303cd03af9 · outbound

This paper cites Adversarially ro- bust representations with smooth encoders,.

Deep Generative Model-Aided Power System Dynamic State Estimation and Reconstruction with Unknown Control Inputs or Data Distributions Adversarially ro- bust representations with smooth encoders,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:06:15.893380Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 65d7f6ca-be44-4a53-a18a-a877e8633fa9 · outbound

This paper cites Elucidating the design space of diffusion-based generative models,.

Deep Generative Model-Aided Power System Dynamic State Estimation and Reconstruction with Unknown Control Inputs or Data Distributions Elucidating the design space of diffusion-based generative models,

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-10T22:06:15.782421Z

Source-reported events for the cited work

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Observation 1ffd3900-403c-42ec-af31-cc5c1b4da827 · outbound

This paper cites Detection and imputation-based two-stage denoising diffusion power system measurement recovery under cyber-physical uncertainties,.

Deep Generative Model-Aided Power System Dynamic State Estimation and Reconstruction with Unknown Control Inputs or Data Distributions Detection and imputation-based two-stage denoising diffusion power system measurement recovery under cyber-physical uncertainties,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:06:15.867486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Pith citing papers

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