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Paper Citation Record · LEDGER

Causal Neural Probabilistic Circuits

As of 9 August 2026, this Paper Citation Record lists 58 of 58 outbound references and 0 inbound Pith citation observations for arXiv:2603.01372.

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

pith.paper-citation-record.v1
2603.01372 v2

Coverage vector

measured 58 of 58 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T19:44:12.974835Z

measured 58 of 58 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Reference resolution

58 of 58 outbound references displayed

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Outbound references

Observation ae5772af-88ce-4e3a-a49c-8f81faa155c5 · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

Causal Neural Probabilistic Circuits Imagenet: A large-scale hierarchical image database

Reference 1

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Observation fd055552-2eca-47ad-8c3b-01a5f9f08825 · outbound

This paper cites an unresolved cited work.

Causal Neural Probabilistic Circuits Unresolved cited work

Reference 2

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Observation 189ed190-2667-40a0-89b2-084f6e537c85 · outbound

This paper cites Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead.Nat.

Causal Neural Probabilistic Circuits Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead.Nat

Reference 3

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Observation 22683ab6-cd1c-44c6-9bca-11423765ba0f · outbound

This paper cites Concept bottleneck models.

Causal Neural Probabilistic Circuits Concept bottleneck models

Reference 4

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Observation 1761c10e-54e0-43f9-bc75-6ee037729bf8 · outbound

This paper cites Right for the right concept: Revising neuro-symbolic concepts by interacting with their explanations.

Causal Neural Probabilistic Circuits Right for the right concept: Revising neuro-symbolic concepts by interacting with their explanations

Reference 5

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Observation e4a4a010-8b5b-4ee3-afc5-cc7c7b2aa66c · outbound

This paper cites Novoa, Justin Ko, Susan M.

Causal Neural Probabilistic Circuits Novoa, Justin Ko, Susan M

Reference 6

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Observation 156b7dea-2982-4100-9550-6b4c70e4aa47 · outbound

This paper cites Clinically applicable deep learning for diagnosis and referral in retinal disease.Nature medicine, 24(9):1342–1350, 2018.

Causal Neural Probabilistic Circuits Clinically applicable deep learning for diagnosis and referral in retinal disease.Nature medicine, 24(9):1342–1350, 2018

Reference 7

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Observation 8707f446-6b10-475d-894f-45cda6800a59 · outbound

This paper cites Concept embedding models: Beyond the accuracy- explainability trade-off.

Causal Neural Probabilistic Circuits Concept embedding models: Beyond the accuracy- explainability trade-off

Reference 8

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Observation 35bd075d-2fd5-4b1d-aac8-69aaef571de4 · outbound

This paper cites Oikarinen, Subhro Das, Lam M.

Causal Neural Probabilistic Circuits Oikarinen, Subhro Das, Lam M

Reference 9

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Observation f0d6e91a-c8b9-4567-abdf-e6d4f1500654 · outbound

This paper cites Causal inference in statistics: An overview.

Causal Neural Probabilistic Circuits Causal inference in statistics: An overview

Reference 10

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Observation 0a2ac6f9-e216-4c5f-887d-333e83ef49a7 · outbound

This paper cites The MIT press, 2017.

Causal Neural Probabilistic Circuits The MIT press, 2017

Reference 11

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Observation bda30270-b9a8-4d5c-a149-b4662989a108 · outbound

This paper cites Neural Probabilistic Circuits: Enabling Compositional and Interpretable Predictions through Logical Reasoning.

Causal Neural Probabilistic Circuits Neural Probabilistic Circuits: Enabling Compositional and Interpretable Predictions through Logical Reasoning

Reference 12

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Observation f69e599e-a664-4924-a7e0-5bd2bbcd3832 · outbound

This paper cites Neural probabilistic circuits: An overview.

Causal Neural Probabilistic Circuits Neural probabilistic circuits: An overview

Reference 13

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Observation 8cbd217d-b3cc-456c-96c5-a69a4ae7ec72 · outbound

This paper cites Domingos.

Causal Neural Probabilistic Circuits Domingos

Reference 14

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source=pdf_text observed=2026-08-02T19:44:09.109194Z digest=sha256:808e561930e24d30c25035b315313fc083e8297148bb5849992a85e558cc2018

Observation 6a66cf56-0db2-464f-b487-595a6dcde3c4 · outbound

This paper cites Probabilistic circuits: A unifying framework for tractable probabilistic models.UCLA.

Causal Neural Probabilistic Circuits Probabilistic circuits: A unifying framework for tractable probabilistic models.UCLA

Reference 15

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Observation 760c6c5e-e54f-4505-8a0c-6449589129fc · outbound

This paper cites Probabilistic circuits: Representations, inference, learning and applications.AAAI Tutorial, 2020.

Causal Neural Probabilistic Circuits Probabilistic circuits: Representations, inference, learning and applications.AAAI Tutorial, 2020

Reference 16

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Observation 9e955c45-78ee-4aee-b106-9c3cacebfe9e · outbound

This paper cites Causal Inference Using Tractable Circuits.

Causal Neural Probabilistic Circuits Causal Inference Using Tractable Circuits

Reference 17

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Observation 63e4bfcc-aca0-4b05-b252-de847d7d50ec · outbound

This paper cites Training products of experts by minimizing contrastive divergence.Neural computation, 14(8):1771–1800, 2002.

Causal Neural Probabilistic Circuits Training products of experts by minimizing contrastive divergence.Neural computation, 14(8):1771–1800, 2002

Reference 18

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Observation dd57ce04-197b-4444-b58b-c459370d7982 · outbound

This paper cites Dietterich.

Causal Neural Probabilistic Circuits Dietterich

Reference 19

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Observation 9bdb9f5b-4c33-48f5-bbf7-a6a8658607a0 · outbound

This paper cites Goodfellow, Jonathon Shlens, and Christian Szegedy.

Causal Neural Probabilistic Circuits Goodfellow, Jonathon Shlens, and Christian Szegedy

Reference 20

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Observation 8c83bddb-f3f0-4f23-8160-4b46a79b6f7d · outbound

This paper cites an unresolved cited work.

Causal Neural Probabilistic Circuits Unresolved cited work

Reference 22

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Observation 744aa4d9-f15f-4c23-8ebe-056f4ca96080 · outbound

This paper cites Addressing leakage in concept bottle- neck models.

Causal Neural Probabilistic Circuits Addressing leakage in concept bottle- neck models

Reference 23

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Observation cbaed461-9699-4e79-af47-6f9bd4cee136 · outbound

This paper cites Causally reliable concept bottleneck models.

Causal Neural Probabilistic Circuits Causally reliable concept bottleneck models

Reference 24

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Observation 162e4cd1-960c-4ad0-abd7-ad49bfd4f2ce · outbound

This paper cites Causal concept graph models: Beyond causal opacity in deep learning.

Causal Neural Probabilistic Circuits Causal concept graph models: Beyond causal opacity in deep learning

Reference 25

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Observation 53aa2109-bf18-44a1-966f-6e037195ea4b · outbound

This paper cites A closer look at the intervention procedure of concept bottleneck models.

Causal Neural Probabilistic Circuits A closer look at the intervention procedure of concept bottleneck models

Reference 26

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Observation 4db8a229-b0ca-47ed-ae50-1b1b9ef5f491 · outbound

This paper cites Learning from uncertain concepts via test time interventions.

Causal Neural Probabilistic Circuits Learning from uncertain concepts via test time interventions

Reference 27

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Observation 28c8278f-c63c-4ced-91f7-7ad3ee143754 · outbound

This paper cites Interactive concept bottleneck models.

Causal Neural Probabilistic Circuits Interactive concept bottleneck models

Reference 28

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Observation c6a7fb75-0833-480e-8884-c2857fd1cb3b · outbound

This paper cites Learning to intervene on concept bottlenecks.

Causal Neural Probabilistic Circuits Learning to intervene on concept bottlenecks

Reference 29

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Observation b12d4a20-7adf-49f5-9934-33c634a9ecf7 · outbound

This paper cites Post-hoc concept bottleneck models.

Causal Neural Probabilistic Circuits Post-hoc concept bottleneck models

Reference 30

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Observation 7922f7bf-1807-4fa3-b626-9a8f68a72c3f · outbound

This paper cites VLG-CBM: training concept bottleneck models with vision-language guidance.

Causal Neural Probabilistic Circuits VLG-CBM: training concept bottleneck models with vision-language guidance

Reference 31

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Observation eb33d9d1-08ca-4b00-921b-458d2cc1725d · outbound

This paper cites Causal diagrams for empirical research.Biometrika, 82(4):669–688, 1995.

Causal Neural Probabilistic Circuits Causal diagrams for empirical research.Biometrika, 82(4):669–688, 1995

Reference 32

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Observation c4db4820-00e5-4da5-8f83-9bea6d5ee6b5 · outbound

This paper cites A general identification condition for causal effects.

Causal Neural Probabilistic Circuits A general identification condition for causal effects

Reference 33

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Observation 159899ca-a42e-4667-9701-cfa7dd0ed296 · outbound

This paper cites An algorithm for fast recovery of sparse causal graphs.Social science computer review, 9(1):62–72, 1991.

Causal Neural Probabilistic Circuits An algorithm for fast recovery of sparse causal graphs.Social science computer review, 9(1):62–72, 1991

Reference 34

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Observation 95fc4485-082f-452b-aafd-356ff61ece7b · outbound

This paper cites Learning bayesian networks: The combination of knowledge and statistical data.Machine learning, 20(3):197–243, 1995.

Causal Neural Probabilistic Circuits Learning bayesian networks: The combination of knowledge and statistical data.Machine learning, 20(3):197–243, 1995

Reference 35

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Observation a693b1bd-5a65-49fb-a187-5a77d67ac723 · outbound

This paper cites Optimal structure identification with greedy search.Journal of machine learning research, 3(Nov):507–554, 2002.

Causal Neural Probabilistic Circuits Optimal structure identification with greedy search.Journal of machine learning research, 3(Nov):507–554, 2002

Reference 36

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Observation 997bcfff-cde0-4d76-a78e-a8dab04f5c50 · outbound

This paper cites Understanding and improving adversarial robustness of neural probabilistic circuits.

Causal Neural Probabilistic Circuits Understanding and improving adversarial robustness of neural probabilistic circuits

Reference 37

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Observation 9b520e4c-dc01-43d5-9af5-6026ef990ab0 · outbound

This paper cites Bucket elimination: A unifying framework for reasoning.Artificial Intelligence, 113(1-2):41–85, 1999.

Causal Neural Probabilistic Circuits Bucket elimination: A unifying framework for reasoning.Artificial Intelligence, 113(1-2):41–85, 1999

Reference 38

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Observation c9caae1d-de0a-4839-afed-c1ec47c3bc41 · outbound

This paper cites MIT press, 2009.

Causal Neural Probabilistic Circuits MIT press, 2009

Reference 39

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Observation 2b0e8dd5-b3a7-4d6b-b152-af0f539847c4 · outbound

This paper cites Cambridge university press, 2009.

Causal Neural Probabilistic Circuits Cambridge university press, 2009

Reference 40

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Observation b1bb5648-a699-45ae-95a5-c5e8f1ff93a6 · outbound

This paper cites Compiling bayesian networks using variable elimination.

Causal Neural Probabilistic Circuits Compiling bayesian networks using variable elimination

Reference 41

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source=pdf_text observed=2026-08-02T19:44:11.338901Z digest=sha256:d772fba4b8f562c6e9c6672b4ff726bdb3590295db50b1575a133aeb6a65ba03

Observation ecf2b00a-52b9-49a8-b602-8aae91171931 · outbound

This paper cites A differential approach to inference in bayesian networks.J.

Causal Neural Probabilistic Circuits A differential approach to inference in bayesian networks.J

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source=pdf_text observed=2026-08-02T19:44:11.431464Z digest=sha256:9284cb1e7b932c9204b470ce90ae453fde87b75baa7a42baabc853f5f4aa4ddd

Observation 83705caa-379f-4c48-917d-5cd66d6eccec · outbound

This paper cites an unresolved cited work.

Causal Neural Probabilistic Circuits Unresolved cited work

Reference 43

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source=pdf_text observed=2026-08-02T19:44:11.502800Z digest=sha256:518468864db84017bd4f2e634af957401982027963c7291f322431cd873b3b42

Observation 34873195-7f9d-4cc8-b2de-df6505cfb453 · outbound

This paper cites Denoising diffusion probabilistic models.

Causal Neural Probabilistic Circuits Denoising diffusion probabilistic models

Reference 44

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source=pdf_text observed=2026-08-02T19:44:11.609466Z digest=sha256:99162cc25ab2bfa56d26a7a136095ba901708f7410f1699201737609ad894db0

Observation 0ff9a27c-5746-4d4c-acc0-66f89ab555e6 · outbound

This paper cites Generative adversarial networks.Communications of the ACM, 63(11):139–144, 2020.

Causal Neural Probabilistic Circuits Generative adversarial networks.Communications of the ACM, 63(11):139–144, 2020

Reference 45

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no resolver link, observed 2026-08-02T19:44:11.705056Z

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source=pdf_text observed=2026-08-02T19:44:11.705056Z digest=sha256:01d40408303baab4afdd248d8bd4fdb25f4885162766f118cdc760a6a0221d20

Observation fa213b71-4bfd-41fc-a167-06bfc3a5f92e · outbound

This paper cites Combining probability distributions: A critique and an annotated bibliography.Statistical Science, 1(1):114–135, 1986.

Causal Neural Probabilistic Circuits Combining probability distributions: A critique and an annotated bibliography.Statistical Science, 1(1):114–135, 1986

Reference 46

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no resolver link, observed 2026-08-02T19:44:11.846173Z

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source=pdf_text observed=2026-08-02T19:44:11.846173Z digest=sha256:8d23da9ed2b92c126c31cae36a29dc13006632a9a1eb1d8bd0ba48f7305a12dd

Observation 8331326f-fd47-48c1-924f-e7618d13fcf3 · outbound

This paper cites Selecting weighting factors in logarithmic opinion pools.

Causal Neural Probabilistic Circuits Selecting weighting factors in logarithmic opinion pools

Reference 47

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source=pdf_text observed=2026-08-02T19:44:11.963676Z digest=sha256:74daef81a39ce781be73b68bdc36ade9b93e65f9eee2f0594ac67edb8343ab65

Observation 1730d79a-9b4f-4e83-98c8-6f878dfa44fa · outbound

This paper cites an unresolved cited work.

Causal Neural Probabilistic Circuits Unresolved cited work

Reference 48

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source=pdf_text observed=2026-08-02T19:44:12.116278Z digest=sha256:1bc8f5196d6d7b7c7d86cd8319ff4dfaff1eae3d1ac24b083372a4be8430aecb

Observation 836448ab-bcd6-48fc-809d-3fa811916323 · outbound

This paper cites Learning bayesian networks with the bnlearn r package.Journal of statistical software, 35:1–22, 2010.

Causal Neural Probabilistic Circuits Learning bayesian networks with the bnlearn r package.Journal of statistical software, 35:1–22, 2010

Reference 49

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source=pdf_text observed=2026-08-02T19:44:12.213215Z digest=sha256:b54e459ec021fb0f081e11a97409673cfee1da7deb95401c5bc36511777b9993

Observation ba0a1e84-d97f-4512-bb19-c4944e08c2ba · outbound

This paper cites Causal protein-signaling networks derived from multiparameter single-cell data.Science, 308(5721): 523–529, 2005.

Causal Neural Probabilistic Circuits Causal protein-signaling networks derived from multiparameter single-cell data.Science, 308(5721): 523–529, 2005

Reference 50

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source=pdf_text observed=2026-08-02T19:44:12.363562Z digest=sha256:06227b98cd0f165fb28b9f88450b24c5615853fbc05331567d40f193410bb264

Observation 2c283c80-2df5-466c-bc58-deca773d2b58 · outbound

This paper cites Deepproblog: Neural probabilistic logic programming.

Causal Neural Probabilistic Circuits Deepproblog: Neural probabilistic logic programming

Reference 51

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source=pdf_text observed=2026-08-02T19:44:12.447800Z digest=sha256:aacc14bb5ea19bb03ce08bfae677d1bc651cbb305be533533e8ebbf17cf6f4f2

Observation 949d2688-ff4c-4af4-8fb7-980449e62683 · outbound

This paper cites Gradient-based learning applied to document recognition.Proceedings of the IEEE, 86(11):2278–2324, 2002.

Causal Neural Probabilistic Circuits Gradient-based learning applied to document recognition.Proceedings of the IEEE, 86(11):2278–2324, 2002

Reference 52

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no resolver link, observed 2026-08-02T19:44:12.517254Z

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source=pdf_text observed=2026-08-02T19:44:12.517254Z digest=sha256:1064dbc0d907ec771376c63e3f5bb6a8f8d4828a45b2fa29f59527f53c10ef7b

Observation ddea5031-633d-4ac2-b3de-4e7072b528b4 · outbound

This paper cites Invariant Risk Minimization.

Causal Neural Probabilistic Circuits Invariant Risk Minimization

Reference 53

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no resolver link, observed 2026-08-02T19:44:12.551132Z

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source=pdf_text observed=2026-08-02T19:44:12.551132Z digest=sha256:ed90e74017a4976e5987f6ab421579439d0e10dd0b4eef5b13639523ca7edb44

Observation 25f524f3-f71e-45b1-80af-c54f99a22f4c · outbound

This paper cites Deep learning face attributes in the wild.

Causal Neural Probabilistic Circuits Deep learning face attributes in the wild

Reference 54

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no resolver link, observed 2026-08-02T19:44:12.618296Z

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source=pdf_text observed=2026-08-02T19:44:12.618296Z digest=sha256:d9002d10038fb612390a89ebc1455f53f985ba8152b6d61dba9da8990540ffcc

Observation d6576c14-e7bc-4f04-9418-a75ba9910e0b · outbound

This paper cites Towards deep learning models resistant to adversarial attacks.

Causal Neural Probabilistic Circuits Towards deep learning models resistant to adversarial attacks

Reference 55

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source=pdf_text observed=2026-08-02T19:44:12.714736Z digest=sha256:3154c68ff85407a66976e28360360bdd74fc954314f8cfef6bf5cfb02aeeaa7d

Observation 75830439-f013-4f64-bf37-270f7600064b · outbound

This paper cites A baseline for detecting misclassified and out-of-distribution examples in neural networks.

Causal Neural Probabilistic Circuits A baseline for detecting misclassified and out-of-distribution examples in neural networks

Reference 56

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source=pdf_text observed=2026-08-02T19:44:12.786319Z digest=sha256:a6b5997389f496eb8f8268ac8f5245ae78adaa226e44f3c1f3cb2be197bd09ab

Observation 9a33f7f0-97bd-46eb-9e11-c3cbb5c4696c · outbound

This paper cites an unresolved cited work.

Causal Neural Probabilistic Circuits Unresolved cited work

Reference 57

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source=pdf_text observed=2026-08-02T19:44:12.844500Z digest=sha256:42359c64020940b3249d5a4cea7549b74ea4231b82552743a519eee46234c659

Observation 32810354-32e6-4026-9e68-39ce61648587 · outbound

This paper cites Domingos.

Causal Neural Probabilistic Circuits Domingos

Reference 58

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source=pdf_text observed=2026-08-02T19:44:12.908993Z digest=sha256:8b789085bacb3b4d46f5360b853c4b77c620545979b9cc3cca3a62071849f4d3

Observation 64d31b75-11c5-4616-8d45-82a1a2b5ea73 · outbound

This paper cites What would the outcome have been had the attribute been set to a different value?.

Causal Neural Probabilistic Circuits What would the outcome have been had the attribute been set to a different value?

Reference 59

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source=pdf_text observed=2026-08-02T19:44:12.974835Z digest=sha256:2103d1118884e38ce016b6cc3e3a19ee2fa4c64a52248c1e903ee25645e64a6a

Pith citing papers

No inbound Pith citation observations are available.