Federated Granger Causality Learning for Interdependent Clients with State Space Representation | Paper Citation Record

Observation 4b8d7dd8-7809-44ad-9afd-a49468c33563 · outbound

This paper cites Brendan McMahan, Ilya Mironov, Kunal Talwar, and Li Zhang.

Federated Granger Causality Learning for Interdependent Clients with State Space Representation Brendan McMahan, Ilya Mironov, Kunal Talwar, and Li Zhang

Reference 1

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Observation 44fd7912-c940-4a1e-baf6-7f83f373ac20 · outbound

This paper cites Learning conditional granger causal temporal networks.

Federated Granger Causality Learning for Interdependent Clients with State Space Representation Learning conditional granger causal temporal networks

Reference 2

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Observation f5810843-f3e6-480f-9e46-b120b3b1b90a · outbound

This paper cites Decentralized supply chains with competing retailers under demand uncertainty.

Federated Granger Causality Learning for Interdependent Clients with State Space Representation Decentralized supply chains with competing retailers under demand uncertainty

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:36:47.572777Z

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This paper cites Stochastic modeling and real-time prognostics for multi-component systems with degradation rate interactions.

Federated Granger Causality Learning for Interdependent Clients with State Space Representation Stochastic modeling and real-time prognostics for multi-component systems with degradation rate interactions

Reference 4

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Observation 9f1a0952-a365-46dd-817a-9707eb826940 · outbound

This paper cites Uncertainty assessment and false discovery rate control in high-dimensional granger causal inference.

Federated Granger Causality Learning for Interdependent Clients with State Space Representation Uncertainty assessment and false discovery rate control in high-dimensional granger causal inference

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:36:47.551804Z

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Observation 90ec1022-ad5b-4db4-a71a-0d87ca173072 · outbound

This paper cites Fedmsplit: Correlation-adaptive federated multi-task learning across multimodal split networks.

Federated Granger Causality Learning for Interdependent Clients with State Space Representation Fedmsplit: Correlation-adaptive federated multi-task learning across multimodal split networks

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:36:47.541479Z

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Observation e7b31fd5-0dea-4bc9-a858-f3b4b4d619e3 · outbound

This paper cites VAFL: a Method of Vertical Asynchronous Federated Learning.

Federated Granger Causality Learning for Interdependent Clients with State Space Representation VAFL: a Method of Vertical Asynchronous Federated Learning

Reference 7

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Observation 8ca0b084-de1e-4081-bfca-57b2f6c80af1 · outbound

This paper cites Distributed kalman filter for large-scale power systems with state inequality constraints.

Federated Granger Causality Learning for Interdependent Clients with State Space Representation Distributed kalman filter for large-scale power systems with state inequality constraints

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-10T15:36:46.302201Z

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Observation 2b6477e8-68a9-42c7-9463-0cf68c1bb83f · outbound

This paper cites The algorithmic foundations of differential privacy.

Federated Granger Causality Learning for Interdependent Clients with State Space Representation The algorithmic foundations of differential privacy

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:36:47.531292Z

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Observation 764637a8-0884-41b4-b754-e130df9ed6c1 · outbound

This paper cites Graphical inference in linear-gaussian state-space models.

Federated Granger Causality Learning for Interdependent Clients with State Space Representation Graphical inference in linear-gaussian state-space models

Reference 10

Resolution: metadata mismatch; raw_fallback, observed 2026-08-10T15:36:47.053247Z

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Observation fe2df561-ff9f-4c11-a0f9-01cb90d43de4 · outbound

This paper cites Large-scale secure xgb for vertical federated learning.

Federated Granger Causality Learning for Interdependent Clients with State Space Representation Large-scale secure xgb for vertical federated learning

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:36:47.521517Z

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Observation 61511105-b0d2-4319-837e-bf952e4ec476 · outbound

This paper cites Partition-based distributed kalman filter with plug and play features.

Federated Granger Causality Learning for Interdependent Clients with State Space Representation Partition-based distributed kalman filter with plug and play features

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:36:47.511159Z

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Observation 84f0bb6f-83cc-42de-bc60-a220f6ce4a32 · outbound

This paper cites Tolerance analysis of cyber-manufacturing systems to cascading failures.

Federated Granger Causality Learning for Interdependent Clients with State Space Representation Tolerance analysis of cyber-manufacturing systems to cascading failures

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:36:47.500037Z

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Observation a01e19d0-e5d0-4c00-b298-c1ee394d2353 · outbound

This paper cites Causal inference by identification of vector autoregressive processes with hidden components.

Federated Granger Causality Learning for Interdependent Clients with State Space Representation Causal inference by identification of vector autoregressive processes with hidden components

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:36:47.489903Z

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Observation bf0a2bc0-66fa-4481-9314-edf9aa594220 · outbound

This paper cites Robust maximum-likelihood estimation of multivariable dynamic systems.

Federated Granger Causality Learning for Interdependent Clients with State Space Representation Robust maximum-likelihood estimation of multivariable dynamic systems

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:36:47.479101Z

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This paper cites Discovering temporal causal relations from subsampled data.

Federated Granger Causality Learning for Interdependent Clients with State Space Representation Discovering temporal causal relations from subsampled data

Reference 16

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Observation e37a5227-3368-424b-b219-a29f99cb82e2 · outbound

This paper cites an unresolved cited work.

Federated Granger Causality Learning for Interdependent Clients with State Space Representation Unresolved cited work

Reference 17

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Observation bdd94aa0-9c38-4e5f-8029-34fa6cf56277 · outbound

This paper cites Privacy-preserving asynchronous vertical federated learning algorithms for multiparty collaborative learning.

Federated Granger Causality Learning for Interdependent Clients with State Space Representation Privacy-preserving asynchronous vertical federated learning algorithms for multiparty collaborative learning

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:36:47.458876Z

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Observation 0a694717-4aa3-421f-a2ef-5956d3e254b1 · outbound

This paper cites Subspace identification of large-scale interconnected systems.

Federated Granger Causality Learning for Interdependent Clients with State Space Representation Subspace identification of large-scale interconnected systems

Reference 19

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Observation 03bd6505-a0e0-49d0-8f7b-499ea830f137 · outbound

This paper cites Private federated learning on vertically partitioned data via entity resolution and additively homomorphic encryption, November 2017.

Federated Granger Causality Learning for Interdependent Clients with State Space Representation Private federated learning on vertically partitioned data via entity resolution and additively homomorphic encryption, November 2017

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:36:47.448682Z

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Observation 6fc0c299-d3e8-4589-bc84-eca75ebad0bd · outbound

This paper cites Fdml: A collaborative machine learning framework for distributed features.

Federated Granger Causality Learning for Interdependent Clients with State Space Representation Fdml: A collaborative machine learning framework for distributed features

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:36:47.438505Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 4db17830-e07c-49a5-920e-6b97c8f0ed1f · outbound

This paper cites Causal discovery and forecasting in nonstationary environments with state-space models.

Federated Granger Causality Learning for Interdependent Clients with State Space Representation Causal discovery and forecasting in nonstationary environments with state-space models

Reference 22

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Observation bdfcab07-50cc-4796-bb24-03fd782f0c41 · outbound

This paper cites an unresolved cited work.

Federated Granger Causality Learning for Interdependent Clients with State Space Representation Unresolved cited work

Reference 23

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Observation cbfd3bf0-3e72-4aab-ab76-9b8d785e696f · outbound

This paper cites Kanat Camlibel.

Federated Granger Causality Learning for Interdependent Clients with State Space Representation Kanat Camlibel

Reference 24

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Observation 857d898d-5972-4be9-8dc0-bec87d9142ee · outbound

This paper cites an unresolved cited work.

Federated Granger Causality Learning for Interdependent Clients with State Space Representation Unresolved cited work

Reference 25

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Observation be98e277-55e0-49c7-9034-a8cacb30f3af · outbound

This paper cites Giannakis.

Federated Granger Causality Learning for Interdependent Clients with State Space Representation Giannakis

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:36:47.386863Z

Source-reported events for the cited work

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Observation ab4b64e3-d03a-41ea-ac29-f457023bbc87 · outbound

This paper cites Splitnet: Learning to semantically split deep networks for parameter reduction and model parallelization.

Federated Granger Causality Learning for Interdependent Clients with State Space Representation Splitnet: Learning to semantically split deep networks for parameter reduction and model parallelization

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:36:47.376951Z

Source-reported events for the cited work

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Observation b6a887c2-a269-4399-91f5-f0b9f94e44bb · outbound

This paper cites Lee and Corey Billington.

Federated Granger Causality Learning for Interdependent Clients with State Space Representation Lee and Corey Billington

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:36:47.366051Z

Source-reported events for the cited work

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Observation f804f4b1-e84c-4070-b6a8-ea570e92b771 · outbound

This paper cites Federated learning of models pre-trained on different features with consensus graphs.

Federated Granger Causality Learning for Interdependent Clients with State Space Representation Federated learning of models pre-trained on different features with consensus graphs

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:36:47.356064Z

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Observation febcd2da-c997-423d-9cfa-2cfed330d065 · outbound

This paper cites Decentralized system identification method for large-scale networks.

Federated Granger Causality Learning for Interdependent Clients with State Space Representation Decentralized system identification method for large-scale networks

Reference 30

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Source-reported events for the cited work

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This paper cites Federated multi-task learning under a mixture of distributions.

Federated Granger Causality Learning for Interdependent Clients with State Space Representation Federated multi-task learning under a mixture of distributions

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:36:47.345668Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 58cf68d2-f9ea-4a5e-bcc4-11eb9ce7f25d · outbound

This paper cites Mathur and Nils Ole Tippenhauer.

Federated Granger Causality Learning for Interdependent Clients with State Space Representation Mathur and Nils Ole Tippenhauer

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:36:47.334620Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 414e178c-0ce4-4ec3-9eaf-47eda8c410b8 · outbound

This paper cites Communication-efficient learning of deep networks from decentralized data.

Federated Granger Causality Learning for Interdependent Clients with State Space Representation Communication-efficient learning of deep networks from decentralized data

Reference 33

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Observation 151541a5-e3f7-4c82-97f5-d96c35e32272 · outbound

This paper cites Okwudire and Harsha V.

Federated Granger Causality Learning for Interdependent Clients with State Space Representation Okwudire and Harsha V

Reference 34

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Observation 7c1ac006-b586-4ae3-bb96-f5c1bfdbe2df · outbound

This paper cites Olfati-Saber.

Federated Granger Causality Learning for Interdependent Clients with State Space Representation Olfati-Saber

Reference 35

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Source-reported events for the cited work

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Observation 1a1b338a-4366-40cd-a61f-a1f4a443303c · outbound

This paper cites Olfati-Saber and J.S.

Federated Granger Causality Learning for Interdependent Clients with State Space Representation Olfati-Saber and J.S

Reference 36

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Observation a4c60fea-9eae-457e-b971-4a9ef7158f80 · outbound

This paper cites Poirot, Praneeth Vepakomma, Ken Chang, Jayashree Kalpathy-Cramer, Rajiv Gupta, and Ramesh Raskar.

Federated Granger Causality Learning for Interdependent Clients with State Space Representation Poirot, Praneeth Vepakomma, Ken Chang, Jayashree Kalpathy-Cramer, Rajiv Gupta, and Ramesh Raskar

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:36:47.283911Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b1b181a0-f656-40d2-b672-1b65787ed8a4 · outbound

This paper cites Hai security datasets, 2023.

Federated Granger Causality Learning for Interdependent Clients with State Space Representation Hai security datasets, 2023

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:36:47.273402Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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This paper cites System identification: Theory for the user, 2nd edition (ljung, l.; 1999) [on the shelf].

Federated Granger Causality Learning for Interdependent Clients with State Space Representation System identification: Theory for the user, 2nd edition (ljung, l.; 1999) [on the shelf]

Reference 39

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Federated Granger Causality Learning for Interdependent Clients with State Space Representation Unresolved cited work

Reference 40

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Observation 1732c164-4e0d-4730-89ad-7fc2d8cfb2e8 · outbound

This paper cites Federated multi-task learning.

Federated Granger Causality Learning for Interdependent Clients with State Space Representation Federated multi-task learning

Reference 41

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation a0457fb2-66a9-4265-b69a-37775583983f · outbound

This paper cites Distributed manufacturing: a new form of localised production? International Journal of Operations & Production Management, 40 0 (6): 0 697–727, January 2020.

Federated Granger Causality Learning for Interdependent Clients with State Space Representation Distributed manufacturing: a new form of localised production? International Journal of Operations & Production Management, 40 0 (6): 0 697–727, January 2020

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:36:47.239947Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation c0d150ec-3674-4f37-a0ae-d320f809602a · outbound

This paper cites Stanković, Srdjan S.

Federated Granger Causality Learning for Interdependent Clients with State Space Representation Stanković, Srdjan S

Reference 43

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 64f0ad8d-213a-4980-a4d2-6a24a65ec22c · outbound

This paper cites Splitfed: When federated learning meets split learning.

Federated Granger Causality Learning for Interdependent Clients with State Space Representation Splitfed: When federated learning meets split learning

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:36:47.214853Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 9802bbc8-9b25-4636-926e-c2e2dac785e0 · outbound

This paper cites Split learning for health: Distributed deep learning without sharing raw patient data, December 2018.

Federated Granger Causality Learning for Interdependent Clients with State Space Representation Split learning for health: Distributed deep learning without sharing raw patient data, December 2018

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:36:47.203406Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation d222001c-f0de-41ee-a86a-a53f0e113deb · outbound

This paper cites Privacy Preserving Vertical Federated Learning for Tree-based Models.

Federated Granger Causality Learning for Interdependent Clients with State Space Representation Privacy Preserving Vertical Federated Learning for Tree-based Models

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-10T15:36:46.450888Z

Source-reported events for the cited work

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Observation 0af65cf6-2d75-4b25-924f-95cdd7f2cb44 · outbound

This paper cites Distributed kalman filter with faulty/reliable sensors based on wasserstein average consensus.

Federated Granger Causality Learning for Interdependent Clients with State Space Representation Distributed kalman filter with faulty/reliable sensors based on wasserstein average consensus

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-10T15:36:46.455228Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af336a6b-03c3-4b56-98de-f93cbdaf65fd · outbound

This paper cites A Quasi-Newton Method Based Vertical Federated Learning Framework for Logistic Regression.

Federated Granger Causality Learning for Interdependent Clients with State Space Representation A Quasi-Newton Method Based Vertical Federated Learning Framework for Logistic Regression

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-10T15:36:46.459313Z

Source-reported events for the cited work

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This paper cites Federated machine learning: Concept and applications.

Federated Granger Causality Learning for Interdependent Clients with State Space Representation Federated machine learning: Concept and applications

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:36:47.190757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 7f85c8d1-f541-488d-a9f0-678900f39c01 · outbound

This paper cites Bayesian nonparametric federated learning of neural networks.

Federated Granger Causality Learning for Interdependent Clients with State Space Representation Bayesian nonparametric federated learning of neural networks

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:36:47.178857Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 231ecf17-032e-4179-9f3b-9079793883ea · outbound

This paper cites an unresolved cited work.

Federated Granger Causality Learning for Interdependent Clients with State Space Representation Unresolved cited work

Reference 51

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 720bd8b5-0791-4525-97d1-ccfcbe1d42c7 · outbound

This paper cites write newline.

Federated Granger Causality Learning for Interdependent Clients with State Space Representation write newline

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-10T15:36:46.477507Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 47cabded-9e92-4d6c-a243-271df6745bd8 · outbound

This paper cites @esa (Ref.

Federated Granger Causality Learning for Interdependent Clients with State Space Representation @esa (Ref

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