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Paper Citation Record · LEDGER

Generative Bayesian Filtering for State Estimation

As of 7 August 2026, this Paper Citation Record lists 100 of 100 outbound references and 0 inbound Pith citation observations for arXiv:2607.20521.

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

pith.paper-citation-record.v1
2607.20521 v1

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measured 100 of 100 reference resolution

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Pith citing papers itemized under the disclosed page cap.

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Reference resolution

100 of 100 outbound references displayed

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Outbound references

Observation 62a26a42-d346-46b5-a11e-1fe315412256 · outbound

This paper cites The American Statistician , volume=.

Generative Bayesian Filtering for State Estimation The American Statistician , volume=

Reference 1

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This paper cites Proceedings of the 28th international conference on machine learning (ICML-11) , pages=.

Generative Bayesian Filtering for State Estimation Proceedings of the 28th international conference on machine learning (ICML-11) , pages=

Reference 2

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This paper cites PLoS One , volume=.

Generative Bayesian Filtering for State Estimation PLoS One , volume=

Reference 3

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This paper cites arXiv preprint arXiv:2604.02222 , year=.

Generative Bayesian Filtering for State Estimation arXiv preprint arXiv:2604.02222 , year=

Reference 4

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Generative Bayesian Filtering for State Estimation IEEE Transactions on Reliability , volume=

Reference 5

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Generative Bayesian Filtering for State Estimation International conference on machine learning , pages=

Reference 6

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Generative Bayesian Filtering for State Estimation International Conference on Machine Learning , pages=

Reference 7

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This paper cites ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) , pages=.

Generative Bayesian Filtering for State Estimation ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) , pages=

Reference 8

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This paper cites 2020 IEEE international workshop on metrology for industry 4.0 & IoT , pages=.

Generative Bayesian Filtering for State Estimation 2020 IEEE international workshop on metrology for industry 4.0 & IoT , pages=

Reference 9

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Generative Bayesian Filtering for State Estimation 2021 , booktitle=

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Generative Bayesian Filtering for State Estimation Biomedical Signal Processing and Control , volume=

Reference 11

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This paper cites Artificial Intelligence Surgery , volume=.

Generative Bayesian Filtering for State Estimation Artificial Intelligence Surgery , volume=

Reference 12

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Generative Bayesian Filtering for State Estimation Science , volume=

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This paper cites Advanced Robotics , volume=.

Generative Bayesian Filtering for State Estimation Advanced Robotics , volume=

Reference 14

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Generative Bayesian Filtering for State Estimation IEEE Transactions on Industrial Informatics , volume=

Reference 15

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Generative Bayesian Filtering for State Estimation Materials Futures , volume=

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Generative Bayesian Filtering for State Estimation Science , volume=

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Generative Bayesian Filtering for State Estimation Additive Manufacturing , pages=

Reference 18

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Generative Bayesian Filtering for State Estimation Learning Representations and Generative Models for 3

Reference 19

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Generative Bayesian Filtering for State Estimation npj Acoustics , volume=

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Generative Bayesian Filtering for State Estimation ACM Computing Surveys , volume=

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Generative Bayesian Filtering for State Estimation Journal of Sensors , volume=

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Generative Bayesian Filtering for State Estimation Proceedings of the 28th international conference on intelligent user interfaces , pages=

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Generative Bayesian Filtering for State Estimation Australian journal of basic and applied sciences , volume=

Reference 24

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Generative Bayesian Filtering for State Estimation IEEE Transactions on industrial electronics , volume=

Reference 25

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Generative Bayesian Filtering for State Estimation International journal of extreme manufacturing , volume=

Reference 26

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Generative Bayesian Filtering for State Estimation International Journal of Precision Engineering and Manufacturing-Green Technology , volume=

Reference 27

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Generative Bayesian Filtering for State Estimation Sensors , volume=

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Generative Bayesian Filtering for State Estimation Multi-Component

Reference 30

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Generative Bayesian Filtering for State Estimation Deep Kalman Filters

Reference 31

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Generative Bayesian Filtering for State Estimation International Conference on Learning Representations , year=

Reference 32

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Generative Bayesian Filtering for State Estimation Advances in Neural Information Processing Systems , volume=

Reference 33

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Generative Bayesian Filtering for State Estimation International Conference on Machine Learning , pages=

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Generative Bayesian Filtering for State Estimation International Conference on Machine Learning , pages=

Reference 35

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Generative Bayesian Filtering for State Estimation , author=

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Generative Bayesian Filtering for State Estimation NeurIPS 2020 Workshop SVRHM , year=

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Generative Bayesian Filtering for State Estimation Auto-Encoding Variational Bayes

Reference 38

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Generative Bayesian Filtering for State Estimation Advances in neural information processing systems , volume=

Reference 39

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Generative Bayesian Filtering for State Estimation International conference on machine learning , pages=

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Generative Bayesian Filtering for State Estimation , title =

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Observation dfdb1a04-6d07-4f0a-ae3e-f458205f4ed4 · outbound

This paper cites Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=.

Generative Bayesian Filtering for State Estimation Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=

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Observation cc939149-2eca-4d0a-b55c-2f31dc981602 · outbound

This paper cites Institute for Systems and Robotics , volume=.

Generative Bayesian Filtering for State Estimation Institute for Systems and Robotics , volume=

Reference 43

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Observation 9c0f4b8d-6552-44ae-b881-ee38b4cf447f · outbound

This paper cites Proceedings of the IEEE 2000 adaptive systems for signal processing, communications, and control symposium (Cat.

Generative Bayesian Filtering for State Estimation Proceedings of the IEEE 2000 adaptive systems for signal processing, communications, and control symposium (Cat

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Observation b7cb1ae7-da27-45d1-bd3d-8351b7991bca · outbound

This paper cites Advances in neural information processing systems , volume=.

Generative Bayesian Filtering for State Estimation Advances in neural information processing systems , volume=

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Observation e2dc05d8-75cc-426e-b25a-e2405a0d6ae8 · outbound

This paper cites IEEE Transactions on Automation Science and Engineering , year=.

Generative Bayesian Filtering for State Estimation IEEE Transactions on Automation Science and Engineering , year=

Reference 46

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Observation 4c710fe2-c50e-4dcf-b5dc-6174324d9f1a · outbound

This paper cites an unresolved cited work.

Generative Bayesian Filtering for State Estimation Unresolved cited work

Reference 47

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source=arxiv_source observed=2026-08-02T08:04:35.081347Z digest=sha256:4daf949cae4c5249417d4cb0a0e13ec665567639b2b50782509a3c58527ba813

Observation a1a4e559-19c5-4932-9b46-0b72412e3d47 · outbound

This paper cites Advances in neural information processing systems , volume=.

Generative Bayesian Filtering for State Estimation Advances in neural information processing systems , volume=

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source=arxiv_source observed=2026-08-02T08:04:35.187411Z digest=sha256:298f91503bd827174f247585736e8ea30d7d20cbea16e21028cf5a59ee4d0b6b

Observation 2f95437a-6256-487d-8599-72049d7e1223 · outbound

This paper cites Stochastic Gradient Langevin Dynamics Algorithms with Adaptive Drifts.

Generative Bayesian Filtering for State Estimation Stochastic Gradient Langevin Dynamics Algorithms with Adaptive Drifts

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source=arxiv_source observed=2026-08-02T08:04:35.229957Z digest=sha256:dc43bbdd339f89b6ae367b1a38824411b22c409f5249ed7ce935bb14220bc437

Observation 14885d19-4093-4417-8d52-b44138809395 · outbound

This paper cites Explaining and Harnessing Adversarial Examples.

Generative Bayesian Filtering for State Estimation Explaining and Harnessing Adversarial Examples

Reference 50

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Observation 1fb3d7f9-a428-4684-9ca3-bb9fafbb786b · outbound

This paper cites 2025 , publisher=.

Generative Bayesian Filtering for State Estimation 2025 , publisher=

Reference 51

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source=arxiv_source observed=2026-08-02T08:04:35.417338Z digest=sha256:1f7a3260047299b20cb77318f2c3db4a7d8cf5e005eb2edb085a03af97192c11

Observation 43c43dc8-c069-4d77-ab77-daa17834f7c0 · outbound

This paper cites Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms.

Generative Bayesian Filtering for State Estimation Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms

Reference 52

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source=arxiv_source observed=2026-08-02T08:04:35.489679Z digest=sha256:51781058ea22e043896b50faa4c60842fdef7035237434d052ed583fb6700190

Observation b26edb51-68b9-485c-a73b-792200f793f7 · outbound

This paper cites IEEE engineering in medicine and biology magazine , volume=.

Generative Bayesian Filtering for State Estimation IEEE engineering in medicine and biology magazine , volume=

Reference 53

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source=arxiv_source observed=2026-08-02T08:04:35.557547Z digest=sha256:2c206130c9eb90b1a32d5e219f6be14157817ffd005514d22ba579cd03a81914

Observation e1174b48-8539-445e-a272-1f784022e290 · outbound

This paper cites 2006 , publisher=.

Generative Bayesian Filtering for State Estimation 2006 , publisher=

Reference 54

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source=arxiv_source observed=2026-08-02T08:04:35.668878Z digest=sha256:c13ed16338c468cfec88e60ff7796cd8748fba8450bf9a76191f03ac24990bd9

Observation 74a3d958-2c18-48ec-a3dc-fb56ee4ad080 · outbound

This paper cites IEEE Transactions on Industrial Informatics , volume=.

Generative Bayesian Filtering for State Estimation IEEE Transactions on Industrial Informatics , volume=

Reference 55

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source=arxiv_source observed=2026-08-02T08:04:35.746245Z digest=sha256:25f6c639806395d3d60b520e12ebfcef431de109e46c96c1f6e094d005f3e028

Observation 8e67887b-a56d-45ca-b913-6d85e2962d31 · outbound

This paper cites Automatica , volume=.

Generative Bayesian Filtering for State Estimation Automatica , volume=

Reference 56

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source=arxiv_source observed=2026-08-02T08:04:35.817137Z digest=sha256:c5d4f0c3d594b0d8a1972758f321c1e9f7914e3777aacefe7a54a12bbb994df9

Observation d67f8821-6984-4b26-b86e-f85b26a0eb2b · outbound

This paper cites Advances in neural information processing systems , volume=.

Generative Bayesian Filtering for State Estimation Advances in neural information processing systems , volume=

Reference 57

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source=arxiv_source observed=2026-08-02T08:04:35.843013Z digest=sha256:bb0a47fcc5f56f430342c1397d862bb057a057296b02cf5931c204864e6f33de

Observation de7fdf0a-7be5-4f67-872e-b6d78b4f4150 · outbound

This paper cites Technometrics , pages=.

Generative Bayesian Filtering for State Estimation Technometrics , pages=

Reference 58

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source=arxiv_source observed=2026-08-02T08:04:35.929985Z digest=sha256:b562d19fae204b90c387b106b9feb2f16e005b80c6817c6cfb755611d90ab7ce

Observation ed85c857-d309-415e-b777-bb64a0bdc13e · outbound

This paper cites GAMM-Mitteilungen , volume=.

Generative Bayesian Filtering for State Estimation GAMM-Mitteilungen , volume=

Reference 59

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source=arxiv_source observed=2026-08-02T08:04:35.984962Z digest=sha256:4a31023b8c197cf505cc26b292e540b873359aba206f442e9e5d05033966d4d4

Observation d4245fec-46fc-4715-9a76-88d85eb6b4e7 · outbound

This paper cites 2025 IEEE Swiss Conference on Data Science (SDS) , pages=.

Generative Bayesian Filtering for State Estimation 2025 IEEE Swiss Conference on Data Science (SDS) , pages=

Reference 60

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source=arxiv_source observed=2026-08-02T08:04:36.034519Z digest=sha256:7436df7a8b0f08212b05296cacce1ff7589d66881d1f45155c0cc0f7b00e5e1a

Observation 931e9093-7b87-4530-ae67-bc8189b53d59 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

Generative Bayesian Filtering for State Estimation Advances in Neural Information Processing Systems , volume=

Reference 61

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source=arxiv_source observed=2026-08-02T08:04:36.070894Z digest=sha256:1f002d32b88be19f1ee1f66571bf7198257aa2fde77930ade3308f8c56ac1fff

Observation b68d826f-dc77-4968-bfc0-ca285b646271 · outbound

This paper cites Computers in Industry , volume=.

Generative Bayesian Filtering for State Estimation Computers in Industry , volume=

Reference 62

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source=arxiv_source observed=2026-08-02T08:04:36.112796Z digest=sha256:4770230456ebc3eb8c60119059dd7002545bcb3c67820c6484ff94eafe541e45

Observation 2d1c2238-7aed-44a2-b906-25bd67b23a45 · outbound

This paper cites IEEE Transactions on Industrial Informatics , volume=.

Generative Bayesian Filtering for State Estimation IEEE Transactions on Industrial Informatics , volume=

Reference 63

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source=arxiv_source observed=2026-08-02T08:04:36.176502Z digest=sha256:c858ede03fa22e7ce014a43017bc184a607445e48451a4db552da00412dab86a

Observation 058e9254-5b22-41aa-98b3-a924080ab843 · outbound

This paper cites Journal of Manufacturing Systems , volume=.

Generative Bayesian Filtering for State Estimation Journal of Manufacturing Systems , volume=

Reference 64

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source=arxiv_source observed=2026-08-02T08:04:36.253164Z digest=sha256:997c7889c94939ff501212b09b6a5a730b95c46bf18c82d5b8e60010b8a9eae5

Observation 49e86ee7-5fa0-42b5-9a03-503ac5f2b32e · outbound

This paper cites Scientific data , volume=.

Generative Bayesian Filtering for State Estimation Scientific data , volume=

Reference 65

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source=arxiv_source observed=2026-08-02T08:04:36.332076Z digest=sha256:a07cd4fb4afc8d5d3c8deb24858a25d69b5cbfcd3e3df74dc5f4c2d484feb8e8

Observation 00f59bb7-147f-4b30-aaf4-7c4209edfddd · outbound

This paper cites BMJ open , volume=.

Generative Bayesian Filtering for State Estimation BMJ open , volume=

Reference 66

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source=arxiv_source observed=2026-08-02T08:04:36.392298Z digest=sha256:fbaa5c8e442bbd98a3e645c321b42194a9cc7e2dcb48a9611aef1bd457142496

Observation 507fb0c0-1cc5-495b-b8bb-2eec83fa84d6 · outbound

This paper cites Journal of Big Data , volume=.

Generative Bayesian Filtering for State Estimation Journal of Big Data , volume=

Reference 67

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source=arxiv_source observed=2026-08-02T08:04:36.450941Z digest=sha256:112d62ee1b0ca45e02d87b22306ebb4eeffc9c168b8f60277208e9ce4cf11531

Observation 6abb93f7-1ca9-4420-bff7-6a4c0c065638 · outbound

This paper cites Archives of Computational Methods in Engineering , volume=.

Generative Bayesian Filtering for State Estimation Archives of Computational Methods in Engineering , volume=

Reference 68

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source=arxiv_source observed=2026-08-02T08:04:36.498389Z digest=sha256:ab33353bda2e6c4ea039150db182aff97c8c8faf62a03767c0156f0a4e98dc48

Observation a8eebba6-2587-4f7f-a0df-e9df9b1470ee · outbound

This paper cites IEEE Access , year=.

Generative Bayesian Filtering for State Estimation IEEE Access , year=

Reference 69

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source=arxiv_source observed=2026-08-02T08:04:36.619857Z digest=sha256:3aea47c418191912508343a407004d36b68ab66f36488cd8154ee73c0f0690b3

Observation dab35c9d-607f-412f-809c-9fbac5bb4334 · outbound

This paper cites Biomimetic Intelligence and Robotics , volume=.

Generative Bayesian Filtering for State Estimation Biomimetic Intelligence and Robotics , volume=

Reference 70

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Observation c21320a9-da96-48d9-b7c6-f81064f04c04 · outbound

This paper cites Proceedings of the IEEE/CVF International Conference on Computer Vision , pages=.

Generative Bayesian Filtering for State Estimation Proceedings of the IEEE/CVF International Conference on Computer Vision , pages=

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Observation d272ed06-28f9-4c34-af8a-8a00216f68cb · outbound

This paper cites stat , volume=.

Generative Bayesian Filtering for State Estimation stat , volume=

Reference 72

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source=arxiv_source observed=2026-08-02T08:04:36.814623Z digest=sha256:7fd5e7e991c4eced2cbdb8f06496625666b4e6b2cecf422f3db26d44c94b220d

Observation 33019568-c2b8-4e00-bc8e-3397c4117474 · outbound

This paper cites Advances in neural information processing systems , volume=.

Generative Bayesian Filtering for State Estimation Advances in neural information processing systems , volume=

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Observation 9be87b39-05e8-4f54-b125-1f753c59b9d9 · outbound

This paper cites International conference on artificial intelligence and statistics , pages=.

Generative Bayesian Filtering for State Estimation International conference on artificial intelligence and statistics , pages=

Reference 74

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source=arxiv_source observed=2026-08-02T08:04:36.994590Z digest=sha256:ae4836fed8f6a73624e1c447935847264188ae4edeb7fa2e2f26bf6e1295aa82

Observation f0fb5cac-d2da-4bd2-9452-8d60bec98840 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

Generative Bayesian Filtering for State Estimation Advances in Neural Information Processing Systems , volume=

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source=arxiv_source observed=2026-08-02T08:04:37.047284Z digest=sha256:2d2f18a99825bd15857e94a411c2bb82c5835437e9e7213ab231963b7ac834c4

Observation e1593a64-325b-4671-be56-b661acd882c1 · outbound

This paper cites Artificial intelligence review , volume=.

Generative Bayesian Filtering for State Estimation Artificial intelligence review , volume=

Reference 76

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source=arxiv_source observed=2026-08-02T08:04:37.123720Z digest=sha256:d3141de07efe101db97695141bd0f14b176bd375fa3f9cd9aae454eb3e297fc2

Observation 60e85c9f-3b3f-45b8-ac87-49aeffbc7d76 · outbound

This paper cites IET control theory & applications , volume=.

Generative Bayesian Filtering for State Estimation IET control theory & applications , volume=

Reference 77

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source=arxiv_source observed=2026-08-02T08:04:37.201799Z digest=sha256:291a476ac65fd546ea9686ee5dcf6e19d8cab3db4dca608069c4873fa5fb9dbd

Observation 6a242d16-d8f3-4314-8a85-21907f08e8aa · outbound

This paper cites IEEE Transactions on Signal Processing , volume=.

Generative Bayesian Filtering for State Estimation IEEE Transactions on Signal Processing , volume=

Reference 78

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source=arxiv_source observed=2026-08-02T08:04:37.301535Z digest=sha256:18004fa2caec32376d0a1400b74261adb5ec124579b7ad2bd4f891051aa8ff9f

Observation 94702719-15c8-48b8-879a-ff738859b705 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

Generative Bayesian Filtering for State Estimation Advances in Neural Information Processing Systems , volume=

Reference 79

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source=arxiv_source observed=2026-08-02T08:04:37.391058Z digest=sha256:d5d3a285bb14c598b7581de0c6495cc26c2e5e5a1375532d62bf5af53e86f8fe

Observation b4377e45-6691-420d-86c1-3819f6000c21 · outbound

This paper cites Entropy , volume=.

Generative Bayesian Filtering for State Estimation Entropy , volume=

Reference 80

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Observation 593bd813-dda4-46e4-aaf2-bd486f938f9e · outbound

This paper cites Advances in neural information processing systems , volume=.

Generative Bayesian Filtering for State Estimation Advances in neural information processing systems , volume=

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Observation 0c3f36f6-1b36-487a-baed-7d7049f2ddc2 · outbound

This paper cites International Conference on Algorithmic Learning Theory , pages=.

Generative Bayesian Filtering for State Estimation International Conference on Algorithmic Learning Theory , pages=

Reference 82

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Observation bd02ff6f-f5a0-4fce-9dd3-e113fc1fd900 · outbound

This paper cites 2019 18th IEEE international conference on machine learning and applications (ICMLA) , pages=.

Generative Bayesian Filtering for State Estimation 2019 18th IEEE international conference on machine learning and applications (ICMLA) , pages=

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Generative Bayesian Filtering for State Estimation Advances in neural information processing systems , volume=

Reference 84

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Generative Bayesian Filtering for State Estimation International Conference on Learning Representations , volume=

Reference 85

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Observation 21283437-d89b-413f-9535-192288d1bce3 · outbound

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Generative Bayesian Filtering for State Estimation SIAM/ASA Journal on Uncertainty Quantification , volume=

Reference 86

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Generative Bayesian Filtering for State Estimation International Conference on Learning Representations , volume=

Reference 87

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Generative Bayesian Filtering for State Estimation International conference on machine learning , pages=

Reference 88

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Generative Bayesian Filtering for State Estimation Neural computation , volume=

Reference 89

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Observation 94dce3c9-8993-4ad9-83a6-dd10810a6d52 · outbound

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Generative Bayesian Filtering for State Estimation Unresolved cited work

Reference 90

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Generative Bayesian Filtering for State Estimation IEEE transactions on biomedical engineering , volume=

Reference 91

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Generative Bayesian Filtering for State Estimation Annual Reviews in Control , volume=

Reference 92

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Generative Bayesian Filtering for State Estimation 2014 , publisher=

Reference 93

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Generative Bayesian Filtering for State Estimation Advances in neural information processing systems , volume=

Reference 94

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Generative Bayesian Filtering for State Estimation Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence , pages =

Reference 95

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Generative Bayesian Filtering for State Estimation Advances in Neural Information Processing Systems , editor=

Reference 96

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Generative Bayesian Filtering for State Estimation 2019 IEEE Intelligent Transportation Systems Conference (ITSC) , pages=

Reference 97

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Generative Bayesian Filtering for State Estimation Proceedings of the IEEE , volume=

Reference 98

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Generative Bayesian Filtering for State Estimation Journal of Basic Engineering , volume=

Reference 99

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Generative Bayesian Filtering for State Estimation Proceedings of the IEEE conference on computer vision and pattern recognition , pages=

Reference 100

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Pith citing papers

No inbound Pith citation observations are available.