Integrating Background Knowledge for Scalable Causal Discovery | Paper Citation Record

Observation e1d69bde-c8ad-4c9d-9f39-a2ac71e5fb2c · outbound

This paper cites Cambridge university press, 2009.

Integrating Background Knowledge for Scalable Causal Discovery Cambridge university press, 2009

Reference 1

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Observation eef8e3fc-e4bd-4d6b-a26a-861510f44bae · outbound

This paper cites Review of causal discovery methods based on graphical models.Frontiers in Genetics, 10, 2019.

Integrating Background Knowledge for Scalable Causal Discovery Review of causal discovery methods based on graphical models.Frontiers in Genetics, 10, 2019

Reference 2

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Observation 5198bb13-8fac-41e3-9285-8372014b5d0c · outbound

This paper cites Maathuis.

Integrating Background Knowledge for Scalable Causal Discovery Maathuis

Reference 3

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This paper cites Inferring causation from time series in earth system sciences.Nature communications, 10(1):2553, 2019.

Integrating Background Knowledge for Scalable Causal Discovery Inferring causation from time series in earth system sciences.Nature communications, 10(1):2553, 2019

Reference 4

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This paper cites Local causal discovery for structural evidence of direct discrimination.Proceedings of the AAAI Conference on Artificial Intelligence, 39(18):19349–19357, Apr.

Integrating Background Knowledge for Scalable Causal Discovery Local causal discovery for structural evidence of direct discrimination.Proceedings of the AAAI Conference on Artificial Intelligence, 39(18):19349–19357, Apr

Reference 5

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This paper cites Causal discovery under a confounder blanket.

Integrating Background Knowledge for Scalable Causal Discovery Causal discovery under a confounder blanket

Reference 6

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Integrating Background Knowledge for Scalable Causal Discovery Unresolved cited work

Reference 7

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This paper cites Snap: Sequential non-ancestor pruning for targeted causal effect estimation with an unknown graph.

Integrating Background Knowledge for Scalable Causal Discovery Snap: Sequential non-ancestor pruning for targeted causal effect estimation with an unknown graph

Reference 8

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This paper cites Discovering and orienting the edges connected to a target variable in a dag via a sequential local learning approach.Computational statistics & data analysis, 77:252–266, 2014.

Integrating Background Knowledge for Scalable Causal Discovery Discovering and orienting the edges connected to a target variable in a dag via a sequential local learning approach.Computational statistics & data analysis, 77:252–266, 2014

Reference 9

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Observation f8d8a409-f6e0-4d52-89cd-2f2a20a97889 · outbound

This paper cites Local causal discovery for estimating causal effects.

Integrating Background Knowledge for Scalable Causal Discovery Local causal discovery for estimating causal effects

Reference 10

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This paper cites Local causal discovery for statistically efficient causal inference.

Integrating Background Knowledge for Scalable Causal Discovery Local causal discovery for statistically efficient causal inference

Reference 11

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Observation 123dd1ff-fc9b-4f94-94dd-c9a55a7b3572 · outbound

This paper cites Maathuis.

Integrating Background Knowledge for Scalable Causal Discovery Maathuis

Reference 12

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Observation e1862a6b-c578-4e7b-beff-5ac132daa518 · outbound

This paper cites On the representation of pairwise causal background knowledge and its applications in causal inference.Journal of Machine Learning Research, 26(229):1–73, 2025.

Integrating Background Knowledge for Scalable Causal Discovery On the representation of pairwise causal background knowledge and its applications in causal inference.Journal of Machine Learning Research, 26(229):1–73, 2025

Reference 13

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Observation 1f38966b-1152-46c4-8e09-1e2d3a9690c7 · outbound

This paper cites Do we become wiser with time? on causal equivalence with tiered background knowledge.

Integrating Background Knowledge for Scalable Causal Discovery Do we become wiser with time? on causal equivalence with tiered background knowledge

Reference 14

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This paper cites Ancestral causal inference.Advances in Neural Information Processing Systems, 29, 2016.

Integrating Background Knowledge for Scalable Causal Discovery Ancestral causal inference.Advances in Neural Information Processing Systems, 29, 2016

Reference 15

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This paper cites Sample efficient active learning of causal trees.

Integrating Background Knowledge for Scalable Causal Discovery Sample efficient active learning of causal trees

Reference 16

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This paper cites Large language models for causal discovery: Current landscape and future directions.

Integrating Background Knowledge for Scalable Causal Discovery Large language models for causal discovery: Current landscape and future directions

Reference 17

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Observation 6c49ae11-9566-45a6-b53e-4ea04d137cce · outbound

This paper cites On the reliability of large language models for causal discovery.

Integrating Background Knowledge for Scalable Causal Discovery On the reliability of large language models for causal discovery

Reference 18

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This paper cites Prior-knowledge-driven local causal structure learning and its application on causal discovery between type 2 diabetes and bone mineral density.IEEE Access, 8:108798–108810,.

Integrating Background Knowledge for Scalable Causal Discovery Prior-knowledge-driven local causal structure learning and its application on causal discovery between type 2 diabetes and bone mineral density.IEEE Access, 8:108798–108810,

Reference 19

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Integrating Background Knowledge for Scalable Causal Discovery Unresolved cited work

Reference 20

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This paper cites Challenges and opportunities with causal discovery algorithms: application to alzheimer’s pathophysiology.Scientific reports, 10(1):2975, 2020.

Integrating Background Knowledge for Scalable Causal Discovery Challenges and opportunities with causal discovery algorithms: application to alzheimer’s pathophysiology.Scientific reports, 10(1):2975, 2020

Reference 21

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This paper cites Reisch, D ´enes Moln´ar, Stefaan De Henauw, Luis Moreno, Toomas Veidebaum, Michael Tornaritis, Iris Pigeot, and Vanessa Didelez.

Integrating Background Knowledge for Scalable Causal Discovery Reisch, D ´enes Moln´ar, Stefaan De Henauw, Luis Moreno, Toomas Veidebaum, Michael Tornaritis, Iris Pigeot, and Vanessa Didelez

Reference 22

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Observation 090ab7d4-e73f-490b-8ed0-3d1ccd71a610 · outbound

This paper cites Constraint-based causal discovery: Conflict resolution with answer set programming.

Integrating Background Knowledge for Scalable Causal Discovery Constraint-based causal discovery: Conflict resolution with answer set programming

Reference 23

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This paper cites Constraint-based causal discovery from multiple interventions over overlapping variable sets.Journal of Machine Learning Research, 16(66): 2147–2205, 2015.

Integrating Background Knowledge for Scalable Causal Discovery Constraint-based causal discovery from multiple interventions over overlapping variable sets.Journal of Machine Learning Research, 16(66): 2147–2205, 2015

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This paper cites Mooij, Sara Magliacane, and Tom Claassen.

Integrating Background Knowledge for Scalable Causal Discovery Mooij, Sara Magliacane, and Tom Claassen

Reference 25

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This paper cites MIT Press, 2nd edition, 2000.

Integrating Background Knowledge for Scalable Causal Discovery MIT Press, 2nd edition, 2000

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This paper cites Causal inference and causal explanation with background knowledge.

Integrating Background Knowledge for Scalable Causal Discovery Causal inference and causal explanation with background knowledge

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Observation 73d08a98-a6b6-49e5-a272-4f932e125682 · outbound

This paper cites Maathuis, and Peter B¨uhlmann.

Integrating Background Knowledge for Scalable Causal Discovery Maathuis, and Peter B¨uhlmann

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Observation 5965af2d-21e0-496c-8682-29d68a250a29 · outbound

This paper cites Causal-learn: Causal discovery in python.Journal of Machine Learning Research, 25(60):1–8, 2024.

Integrating Background Knowledge for Scalable Causal Discovery Causal-learn: Causal discovery in python.Journal of Machine Learning Research, 25(60):1–8, 2024

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This paper cites Tetrad—a toolbox for causal discovery.8th international workshop on climate informatics, 2018.

Integrating Background Knowledge for Scalable Causal Discovery Tetrad—a toolbox for causal discovery.8th international workshop on climate informatics, 2018

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This paper cites pgmpy: A python toolkit for bayesian networks.Journal of Machine Learning Research, 25(265):1–8, 2024.

Integrating Background Knowledge for Scalable Causal Discovery pgmpy: A python toolkit for bayesian networks.Journal of Machine Learning Research, 25(265):1–8, 2024

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This paper cites Learning high-dimensional directed acyclic graphs with latent and selection variables.The Annals of Statistics, pages 294–321, 2012.

Integrating Background Knowledge for Scalable Causal Discovery Learning high-dimensional directed acyclic graphs with latent and selection variables.The Annals of Statistics, pages 294–321, 2012

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This paper cites Bayesian network induction via local neighborhoods.

Integrating Background Knowledge for Scalable Causal Discovery Bayesian network induction via local neighborhoods

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This paper cites Using markov blankets for causal structure learning.

Integrating Background Knowledge for Scalable Causal Discovery Using markov blankets for causal structure learning

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This paper cites Local Causal Discovery with Background Knowledge .IEEE Transactions on Pattern Analysis & Machine Intelligence, pages 1– 12, February 2026.

Integrating Background Knowledge for Scalable Causal Discovery Local Causal Discovery with Background Knowledge .IEEE Transactions on Pattern Analysis & Machine Intelligence, pages 1– 12, February 2026

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This paper cites Improving Finite Sample Performance of Causal Discovery by Exploiting Temporal Structure.

Integrating Background Knowledge for Scalable Causal Discovery Improving Finite Sample Performance of Causal Discovery by Exploiting Temporal Structure

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Integrating Background Knowledge for Scalable Causal Discovery Unresolved cited work

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This paper cites Constraint-based causal discovery with tiered back- ground knowledge and latent variables in single or overlapping datasets.Proceedings of Machine Learning Research, 275:1–31, 2025.

Integrating Background Knowledge for Scalable Causal Discovery Constraint-based causal discovery with tiered back- ground knowledge and latent variables in single or overlapping datasets.Proceedings of Machine Learning Research, 275:1–31, 2025

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This paper cites Score-Based Causal Discovery with Temporal Background Information.

Integrating Background Knowledge for Scalable Causal Discovery Score-Based Causal Discovery with Temporal Background Information

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This paper cites Sound and complete causal identification with latent variables given local background knowledge.Artificial Intelligence, 322:103964,.

Integrating Background Knowledge for Scalable Causal Discovery Sound and complete causal identification with latent variables given local background knowledge.Artificial Intelligence, 322:103964,

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This paper cites doi: https://doi.org/10.1016/j.artint.2023.103964.

Integrating Background Knowledge for Scalable Causal Discovery doi: https://doi.org/10.1016/j.artint.2023.103964

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This paper cites Towards Complete Causal Explanation with Expert Knowledge.

Integrating Background Knowledge for Scalable Causal Discovery Towards Complete Causal Explanation with Expert Knowledge

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This paper cites A logical characterization of constraint-based causal discovery.

Integrating Background Knowledge for Scalable Causal Discovery A logical characterization of constraint-based causal discovery

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This paper cites A hybrid algorithm for learning causal networks using uncertain experts’ knowledge.

Integrating Background Knowledge for Scalable Causal Discovery A hybrid algorithm for learning causal networks using uncertain experts’ knowledge

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Integrating Background Knowledge for Scalable Causal Discovery Unresolved cited work

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This paper cites Mitigating prior errors in causal structure learning: A resilient approach via bayesian networks.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2025.

Integrating Background Knowledge for Scalable Causal Discovery Mitigating prior errors in causal structure learning: A resilient approach via bayesian networks.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2025

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This paper cites Causal discovery with language models as imperfect experts.

Integrating Background Knowledge for Scalable Causal Discovery Causal discovery with language models as imperfect experts

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Observation 5063fc22-da76-4b18-b3ac-bdcea7ab5e08 · outbound

This paper cites Integrating large language models in causal discovery: A statistical causal approach.Transactions on Machine Learning Research, 2025.

Integrating Background Knowledge for Scalable Causal Discovery Integrating large language models in causal discovery: A statistical causal approach.Transactions on Machine Learning Research, 2025

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This paper cites Llm-initialized differentiable causal discovery.

Integrating Background Knowledge for Scalable Causal Discovery Llm-initialized differentiable causal discovery

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This paper cites Large- scale hierarchical causal discovery via weak prior knowledge.IEEE Transactions on Knowledge and Data Engineering, 37(5):2695–2711, 2025.

Integrating Background Knowledge for Scalable Causal Discovery Large- scale hierarchical causal discovery via weak prior knowledge.IEEE Transactions on Knowledge and Data Engineering, 37(5):2695–2711, 2025

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This paper cites From guess2graph: When and how can unreliable experts safely boost causal discovery in finite samples?arXiv preprint arXiv:2510.14488, 2025.

Integrating Background Knowledge for Scalable Causal Discovery From guess2graph: When and how can unreliable experts safely boost causal discovery in finite samples?arXiv preprint arXiv:2510.14488, 2025

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Integrating Background Knowledge for Scalable Causal Discovery Unresolved cited work

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Integrating Background Knowledge for Scalable Causal Discovery Unresolved cited work

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This paper cites Learning bayesian networks with the bnlearn R package.Journal of Statistical Software, 35(3):1–22, 2010.

Integrating Background Knowledge for Scalable Causal Discovery Learning bayesian networks with the bnlearn R package.Journal of Statistical Software, 35(3):1–22, 2010

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This paper cites Clarendon Press, 1996.

Integrating Background Knowledge for Scalable Causal Discovery Clarendon Press, 1996

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This paper cites Variable elimination, graph reduction and the efficient g-formula.Biometrika, 110(3):739–761, 2023.

Integrating Background Knowledge for Scalable Causal Discovery Variable elimination, graph reduction and the efficient g-formula.Biometrika, 110(3):739–761, 2023

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Observation 7b324853-fca2-45d3-a833-def6f1c7cae1 · outbound

This paper cites Maathuis, and Vanessa Didelez.

Integrating Background Knowledge for Scalable Causal Discovery Maathuis, and Vanessa Didelez

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Observation 044d4857-b36e-4d5e-8f57-af9a99e5885f · outbound

This paper cites A local method for identifying causal relations under markov equivalence.Artificial Intelligence, 305:103669,.

Integrating Background Knowledge for Scalable Causal Discovery A local method for identifying causal relations under markov equivalence.Artificial Intelligence, 305:103669,

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Observation 401f1787-50ab-4ab1-b2a6-caf2566f430b · outbound

This paper cites doi: https://doi.org/10.1016/j.artint.2022.103669.

Integrating Background Knowledge for Scalable Causal Discovery doi: https://doi.org/10.1016/j.artint.2022.103669

Reference 59

Resolution: verified exact; arxiv_id, observed 2026-07-14T11:40:26.060450Z

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 950ffa32-f706-41f8-95e2-5770fdf52412 · outbound

This paper cites The igraph software package for complex network research.

Integrating Background Knowledge for Scalable Causal Discovery The igraph software package for complex network research

Reference 60

Resolution: unresolved; no resolver link, observed 2026-07-14T11:35:13.719704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b5931643-d56d-4e26-a72c-a39ab2fc9df6 · outbound

This paper cites Exploring network structure, dynamics, and function using networkx.

Integrating Background Knowledge for Scalable Causal Discovery Exploring network structure, dynamics, and function using networkx

Reference 61

Resolution: unresolved; no resolver link, observed 2026-07-14T11:35:13.719704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation da374904-e0a8-4436-b00a-e4f29c81af4f · outbound

This paper cites an unresolved cited work.

Integrating Background Knowledge for Scalable Causal Discovery Unresolved cited work

Reference 62

Resolution: unresolved; no resolver link, observed 2026-07-14T11:35:13.719704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 814e10c6-5cf6-4f9a-9a8d-8dcf65f727cc · outbound

This paper cites The first difference impacts all pairs (X, Y)∈ B.

Integrating Background Knowledge for Scalable Causal Discovery The first difference impacts all pairs (X, Y)∈ B

Reference 63

Resolution: unresolved; no resolver link, observed 2026-07-14T11:35:13.719704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0a5fc403-e058-44da-8bd1-8deb4df06a7a · outbound

This paper cites 2b, since all variables are marginally dependent.

Integrating Background Knowledge for Scalable Causal Discovery 2b, since all variables are marginally dependent

Reference 64

Resolution: unresolved; no resolver link, observed 2026-07-14T11:35:13.719704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f0e67ca8-dfdf-4341-8b6e-1d39baa2a61d · outbound

This paper cites an unresolved cited work.

Integrating Background Knowledge for Scalable Causal Discovery Unresolved cited work

Reference 65

Resolution: unresolved; no resolver link, observed 2026-07-14T11:35:13.719704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f9fd3a77-ea73-480e-b4c1-a8905e4b086f · outbound

This paper cites an unresolved cited work.

Integrating Background Knowledge for Scalable Causal Discovery Unresolved cited work

Reference 66

Resolution: unresolved; no resolver link, observed 2026-07-14T11:35:13.719704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6a1f97bc-9d52-43fd-a359-fbe63f7cafc0 · outbound

This paper cites an unresolved cited work.

Integrating Background Knowledge for Scalable Causal Discovery Unresolved cited work

Reference 67

Resolution: unresolved; no resolver link, observed 2026-07-14T11:35:13.719704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d72c6f71-ca4e-40c6-adc6-e73262ea01f3 · outbound

This paper cites Then, because Z→X , it follows that Z∈V ∗.

Integrating Background Knowledge for Scalable Causal Discovery Then, because Z→X , it follows that Z∈V ∗

Reference 68

Resolution: unresolved; no resolver link, observed 2026-07-14T11:35:13.719704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b087d8a5-70e3-458a-8302-d6f7def15b39 · outbound

This paper cites Then, because Z→Y , it follows that Z∈V ∗.

Integrating Background Knowledge for Scalable Causal Discovery Then, because Z→Y , it follows that Z∈V ∗

Reference 69

Resolution: unresolved; no resolver link, observed 2026-07-14T11:35:13.719704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 44c2c0d6-f447-4355-b1f5-0b68f852cf8e · outbound

This paper cites Then, due to V→Y←Z, it follows thatV, Z∈V ∗.

Integrating Background Knowledge for Scalable Causal Discovery Then, due to V→Y←Z, it follows thatV, Z∈V ∗

Reference 70

Resolution: unresolved; no resolver link, observed 2026-07-14T11:35:13.719704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6f98188b-5a18-4a30-941c-20962ac7e30e · outbound

This paper cites Then, because X−VandZ→Y, it follows thatV, Z∈V ∗.

Integrating Background Knowledge for Scalable Causal Discovery Then, because X−VandZ→Y, it follows thatV, Z∈V ∗

Reference 71

Resolution: unresolved; no resolver link, observed 2026-07-14T11:35:13.719704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95ae17dd-a162-41b7-ab5e-12b9d4e45bda · outbound

This paper cites an unresolved cited work.

Integrating Background Knowledge for Scalable Causal Discovery Unresolved cited work

Reference 72

Resolution: unresolved; no resolver link, observed 2026-07-14T11:35:13.719704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 87903215-c98d-4adc-88e6-8788a1755c9c · outbound

This paper cites an unresolved cited work.

Integrating Background Knowledge for Scalable Causal Discovery Unresolved cited work

Reference 73

Resolution: unresolved; no resolver link, observed 2026-07-14T11:35:13.719704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a7010f39-985a-4800-bb78-c26699b9b01b · outbound

This paper cites an unresolved cited work.

Integrating Background Knowledge for Scalable Causal Discovery Unresolved cited work

Reference 74

Resolution: unresolved; no resolver link, observed 2026-07-14T11:35:13.719704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4fddbeb1-e2bd-464f-9e51-6701e053cdeb · outbound

This paper cites The reason why using the PC v-structure orientation rules at order i= 1 in SNAP(k)-BK can fail is because the case of orderi= 1in Lem.

Integrating Background Knowledge for Scalable Causal Discovery The reason why using the PC v-structure orientation rules at order i= 1 in SNAP(k)-BK can fail is because the case of orderi= 1in Lem

Reference 75

Resolution: unresolved; no resolver link, observed 2026-07-14T11:35:13.719704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 15271673-0896-448f-bc73-8b02546f2bfb · outbound

This paper cites an unresolved cited work.

Integrating Background Knowledge for Scalable Causal Discovery Unresolved cited work

Reference 76

Resolution: unresolved; no resolver link, observed 2026-07-14T11:35:13.719704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 35f5c0a7-62f2-4930-8bd1-0a51609eba57 · outbound

This paper cites an unresolved cited work.

Integrating Background Knowledge for Scalable Causal Discovery Unresolved cited work

Reference 77

Resolution: unresolved; no resolver link, observed 2026-07-14T11:35:13.719704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fdfdd534-601f-4b7c-95cc-012031e47fda · outbound

This paper cites (b) When trying to separate nodes fromX, PC-BK also does not findX⊥ ⊥T|{V2} because V2 /∈PossPaLT (X,B)due toX̸−V 2 ∈ B.

Integrating Background Knowledge for Scalable Causal Discovery (b) When trying to separate nodes fromX, PC-BK also does not findX⊥ ⊥T|{V2} because V2 /∈PossPaLT (X,B)due toX̸−V 2 ∈ B

Reference 78

Resolution: unresolved; no resolver link, observed 2026-07-14T11:35:13.719704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cf54475d-29df-48d5-ae42-827b065b910c · outbound

This paper cites an unresolved cited work.

Integrating Background Knowledge for Scalable Causal Discovery Unresolved cited work

Reference 79

Resolution: unresolved; no resolver link, observed 2026-07-14T11:35:13.719704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 51b2eaf3-aa9d-4328-8cc8-7fa84009bf6d · outbound

This paper cites an unresolved cited work.

Integrating Background Knowledge for Scalable Causal Discovery Unresolved cited work

Reference 80

Resolution: unresolved; no resolver link, observed 2026-07-14T11:35:13.719704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8ca0047a-d9ad-46d0-9d43-8d4d409e6e99 · outbound

This paper cites an unresolved cited work.

Integrating Background Knowledge for Scalable Causal Discovery Unresolved cited work

Reference 81

Resolution: unresolved; no resolver link, observed 2026-07-14T11:35:13.719704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 36f5fe3f-ce58-46f1-9cbe-f10fa1278156 · outbound

This paper cites Instead, if PC-BK uses the adjusted definition of possible parents defined in Equation(1), then the MB-by-MB-BK algorithm would proceed as follows:.

Integrating Background Knowledge for Scalable Causal Discovery Instead, if PC-BK uses the adjusted definition of possible parents defined in Equation(1), then the MB-by-MB-BK algorithm would proceed as follows:

Reference 82

Resolution: unresolved; no resolver link, observed 2026-07-14T11:35:13.719704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e64e3d5e-21bc-4e1e-9088-fd5be3e43992 · outbound

This paper cites an unresolved cited work.

Integrating Background Knowledge for Scalable Causal Discovery Unresolved cited work

Reference 83

Resolution: unresolved; no resolver link, observed 2026-07-14T11:35:13.719704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 313037a7-5116-4f43-a04f-8f975e35649f · outbound

This paper cites an unresolved cited work.

Integrating Background Knowledge for Scalable Causal Discovery Unresolved cited work

Reference 84

Resolution: unresolved; no resolver link, observed 2026-07-14T11:35:13.719704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4fc6980d-c1bf-46cc-a0ca-62507d932a2e · outbound

This paper cites (b) When trying to separate nodes from X at i= 1 of the skeleton search of PC-BK, at this point X and V2 are adjacent, and so V2 ∈PossPa ∗ ˆG(X,B) =Ad j ˆG(X).

Integrating Background Knowledge for Scalable Causal Discovery (b) When trying to separate nodes from X at i= 1 of the skeleton search of PC-BK, at this point X and V2 are adjacent, and so V2 ∈PossPa ∗ ˆG(X,B) =Ad j ˆG(X)

Reference 85

Resolution: unresolved; no resolver link, observed 2026-07-14T11:35:13.719704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 273a93ba-030a-419a-a897-3d0cb3e119ab · outbound

This paper cites an unresolved cited work.

Integrating Background Knowledge for Scalable Causal Discovery Unresolved cited work

Reference 86

Resolution: unresolved; no resolver link, observed 2026-07-14T11:35:13.719704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cc148d6b-96e7-454e-a666-aa9c0a961d77 · outbound

This paper cites an unresolved cited work.

Integrating Background Knowledge for Scalable Causal Discovery Unresolved cited work

Reference 87

Resolution: unresolved; no resolver link, observed 2026-07-14T11:35:13.719704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 090fbd89-60da-4a01-a26f-77a1df3eea4c · outbound

This paper cites Theorem 3.3.Given oracle CI tests and consistent BK, MB-by-MB-BK is sound and complete in identifying the parents, children and siblings of the target.

Integrating Background Knowledge for Scalable Causal Discovery Theorem 3.3.Given oracle CI tests and consistent BK, MB-by-MB-BK is sound and complete in identifying the parents, children and siblings of the target

Reference 88

Resolution: unresolved; no resolver link, observed 2026-07-14T11:35:13.719704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3a69c609-1915-4493-a401-ba93b89b7ccb · outbound

This paper cites an unresolved cited work.

Integrating Background Knowledge for Scalable Causal Discovery Unresolved cited work

Reference 89

Resolution: unresolved; no resolver link, observed 2026-07-14T11:35:13.719704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 24e44a83-fe15-4fb7-ad35-2821add75596 · outbound

This paper cites an unresolved cited work.

Integrating Background Knowledge for Scalable Causal Discovery Unresolved cited work

Reference 90

Resolution: unresolved; no resolver link, observed 2026-07-14T11:35:13.719704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5d0d8177-5559-4f3a-b4ce-cec7adc843da · outbound

This paper cites an unresolved cited work.

Integrating Background Knowledge for Scalable Causal Discovery Unresolved cited work

Reference 91

Resolution: unresolved; no resolver link, observed 2026-07-14T11:35:13.719704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e4323fbd-743e-4d66-91b6-1e2db90583fd · outbound

This paper cites an unresolved cited work.

Integrating Background Knowledge for Scalable Causal Discovery Unresolved cited work

Reference 92

Resolution: unresolved; no resolver link, observed 2026-07-14T11:35:13.719704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dbc41244-4eaa-4473-a415-aed89dd630eb · outbound

This paper cites Note, that LDECC-BK would also return Y as a sibling of T if it did not skip CI tests for X and Y.

Integrating Background Knowledge for Scalable Causal Discovery Note, that LDECC-BK would also return Y as a sibling of T if it did not skip CI tests for X and Y

Reference 93

Resolution: unresolved; no resolver link, observed 2026-07-14T11:35:13.719704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4bd73188-e48a-4710-9213-aaba857abf3a · outbound

This paper cites an unresolved cited work.

Integrating Background Knowledge for Scalable Causal Discovery Unresolved cited work

Reference 94

Resolution: unresolved; no resolver link, observed 2026-07-14T11:35:13.719704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 96fc3616-4c3e-4c1d-8911-0bbe4087d6a1 · outbound

This paper cites an unresolved cited work.

Integrating Background Knowledge for Scalable Causal Discovery Unresolved cited work

Reference 95

Resolution: unresolved; no resolver link, observed 2026-07-14T11:35:13.719704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5b73f5d2-96f3-40ad-a85a-db63238d60e1 · outbound

This paper cites graphNEL.

Integrating Background Knowledge for Scalable Causal Discovery graphNEL

Reference 96

Resolution: malformed identifier; no resolver link, observed 2026-07-14T11:35:13.719704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a4448a6c-ae08-4963-bd0f-9b119ca1d237 · outbound

This paper cites Guidelines: • The answer [N/A] means that the paper does not involve crowdsourcing nor research with human subjects.

Integrating Background Knowledge for Scalable Causal Discovery Guidelines: • The answer [N/A] means that the paper does not involve crowdsourcing nor research with human subjects

Reference 97

Resolution: unresolved; no resolver link, observed 2026-07-14T11:35:13.719704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

Reference resolution

Outbound references

Pith citing papers