A Compositional Theory of Curvature in Probabilistic Circuits | Paper Citation Record

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This paper cites Relative Flatness and Generalization , year =.

A Compositional Theory of Curvature in Probabilistic Circuits Relative Flatness and Generalization , year =

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A Compositional Theory of Curvature in Probabilistic Circuits Forty-third International Conference on Machine Learning , year=

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This paper cites Proceedings of the 40th International Conference on Machine Learning , pages =.

A Compositional Theory of Curvature in Probabilistic Circuits Proceedings of the 40th International Conference on Machine Learning , pages =

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

A Compositional Theory of Curvature in Probabilistic Circuits Advances in Neural Information Processing Systems , volume=

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A Compositional Theory of Curvature in Probabilistic Circuits International Conference on Machine Learning , pages=

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A Compositional Theory of Curvature in Probabilistic Circuits International Conference on Learning Representations , year=

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This paper cites 5th International Conference on Learning Representations, 2017 , title =.

A Compositional Theory of Curvature in Probabilistic Circuits 5th International Conference on Learning Representations, 2017 , title =

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This paper cites Tractable Control for Autoregressive Language Generation , year =.

A Compositional Theory of Curvature in Probabilistic Circuits Tractable Control for Autoregressive Language Generation , year =

Reference 8

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This paper cites AAAI Conference on Artificial Intelligence, 2025 , volume=.

A Compositional Theory of Curvature in Probabilistic Circuits AAAI Conference on Artificial Intelligence, 2025 , volume=

Reference 9

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Observation ac589752-7a9f-4787-a7fc-f6d55f237db7 · outbound

This paper cites How to Turn Your Knowledge Graph Embeddings into Generative Models via Probabilistic Circuits , year =.

A Compositional Theory of Curvature in Probabilistic Circuits How to Turn Your Knowledge Graph Embeddings into Generative Models via Probabilistic Circuits , year =

Reference 10

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This paper cites Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022 , title =.

A Compositional Theory of Curvature in Probabilistic Circuits Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022 , title =

Reference 11

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Observation 068e3d2e-b394-4a25-85bc-fbd4930c242c · outbound

This paper cites Probabilistic circuits that know what they don't know , year =.

A Compositional Theory of Curvature in Probabilistic Circuits Probabilistic circuits that know what they don't know , year =

Reference 12

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This paper cites The 28th International Conference on Artificial Intelligence and Statistics , year =.

A Compositional Theory of Curvature in Probabilistic Circuits The 28th International Conference on Artificial Intelligence and Statistics , year =

Reference 13

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Observation f048fc12-a904-4ec9-a3b0-0ce0a876518e · outbound

This paper cites Image Inpainting via Tractable Steering of Diffusion Models , year =.

A Compositional Theory of Curvature in Probabilistic Circuits Image Inpainting via Tractable Steering of Diffusion Models , year =

Reference 14

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This paper cites Balasubramanian , bibsource =.

A Compositional Theory of Curvature in Probabilistic Circuits Balasubramanian , bibsource =

Reference 15

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This paper cites Lipton , booktitle =.

A Compositional Theory of Curvature in Probabilistic Circuits Lipton , booktitle =

Reference 16

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This paper cites Ugur Güney and Yann Dauphin and Léon Bottou , booktitle =.

A Compositional Theory of Curvature in Probabilistic Circuits Ugur Güney and Yann Dauphin and Léon Bottou , booktitle =

Reference 17

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Observation 3b56c767-322b-4132-b2b4-25cc36b7c567 · outbound

This paper cites Asymmetric Valleys: Beyond Sharp and Flat Local Minima , year =.

A Compositional Theory of Curvature in Probabilistic Circuits Asymmetric Valleys: Beyond Sharp and Flat Local Minima , year =

Reference 18

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Observation c0967781-97ad-4740-8326-7ccf0f5d064e · outbound

This paper cites Improving Generalization in Federated Learning by Seeking Flat Minima , year =.

A Compositional Theory of Curvature in Probabilistic Circuits Improving Generalization in Federated Learning by Seeking Flat Minima , year =

Reference 19

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This paper cites Geometry of the Loss Landscape in Overparameterized Neural Networks: Symmetries and Invariances , year =.

A Compositional Theory of Curvature in Probabilistic Circuits Geometry of the Loss Landscape in Overparameterized Neural Networks: Symmetries and Invariances , year =

Reference 20

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This paper cites SIAM Journal on Mathematics of Data Science , title =.

A Compositional Theory of Curvature in Probabilistic Circuits SIAM Journal on Mathematics of Data Science , title =

Reference 21

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This paper cites Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, , title =.

A Compositional Theory of Curvature in Probabilistic Circuits Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, , title =

Reference 22

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This paper cites Variational Inference with Normalizing Flows , year =.

A Compositional Theory of Curvature in Probabilistic Circuits Variational Inference with Normalizing Flows , year =

Reference 23

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This paper cites Gradient Norm Aware Minimization Seeks First-Order Flatness and Improves Generalization , year =.

A Compositional Theory of Curvature in Probabilistic Circuits Gradient Norm Aware Minimization Seeks First-Order Flatness and Improves Generalization , year =

Reference 24

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This paper cites 38th International Conference on Machine Learning, 2021 , pages =.

A Compositional Theory of Curvature in Probabilistic Circuits 38th International Conference on Machine Learning, 2021 , pages =

Reference 25

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This paper cites Building Expressive and Tractable Probabilistic Generative Models:.

A Compositional Theory of Curvature in Probabilistic Circuits Building Expressive and Tractable Probabilistic Generative Models:

Reference 26

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This paper cites Cutset networks: A simple, tractable, and scalable approach for improving the accuracy of chow-liu trees , year =.

A Compositional Theory of Curvature in Probabilistic Circuits Cutset networks: A simple, tractable, and scalable approach for improving the accuracy of chow-liu trees , year =

Reference 27

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This paper cites A Differential Approach to Inference in Bayesian Networks , year =.

A Compositional Theory of Curvature in Probabilistic Circuits A Differential Approach to Inference in Bayesian Networks , year =

Reference 28

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Observation 0784dc4e-c426-42c0-b236-f1b7dde4f729 · outbound

This paper cites Sharpness-aware Minimization for Efficiently Improving Generalization , year =.

A Compositional Theory of Curvature in Probabilistic Circuits Sharpness-aware Minimization for Efficiently Improving Generalization , year =

Reference 29

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This paper cites Scaling Probabilistic Circuits via Monarch Matrices , year =.

A Compositional Theory of Curvature in Probabilistic Circuits Scaling Probabilistic Circuits via Monarch Matrices , year =

Reference 30

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This paper cites Visualizing the Loss Landscape of Neural Nets , year =.

A Compositional Theory of Curvature in Probabilistic Circuits Visualizing the Loss Landscape of Neural Nets , year =

Reference 31

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This paper cites Flat minima , year =.

A Compositional Theory of Curvature in Probabilistic Circuits Flat minima , year =

Reference 32

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This paper cites Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning , year =.

A Compositional Theory of Curvature in Probabilistic Circuits Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning , year =

Reference 33

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This paper cites Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits , year =.

A Compositional Theory of Curvature in Probabilistic Circuits Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits , year =

Reference 34

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This paper cites Strudel: Learning Structured-Decomposable Probabilistic Circuits , year =.

A Compositional Theory of Curvature in Probabilistic Circuits Strudel: Learning Structured-Decomposable Probabilistic Circuits , year =

Reference 35

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This paper cites de Campos and Robert Peharz and Antonio Vergari and Erik Quaeghebeur , bibsource =.

A Compositional Theory of Curvature in Probabilistic Circuits de Campos and Robert Peharz and Antonio Vergari and Erik Quaeghebeur , bibsource =

Reference 36

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This paper cites Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems, 2022 , title =.

A Compositional Theory of Curvature in Probabilistic Circuits Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems, 2022 , title =

Reference 37

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This paper cites The Eleventh International Conference on Learning Representations, 2023 , title =.

A Compositional Theory of Curvature in Probabilistic Circuits The Eleventh International Conference on Learning Representations, 2023 , title =

Reference 38

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This paper cites Sum of squares circuits , year =.

A Compositional Theory of Curvature in Probabilistic Circuits Sum of squares circuits , year =

Reference 39

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This paper cites Transactions on Machine Learning Research , issn=.

A Compositional Theory of Curvature in Probabilistic Circuits Transactions on Machine Learning Research , issn=

Reference 40

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A Compositional Theory of Curvature in Probabilistic Circuits Sladek and Stefan Mengel and Martin Trapp and Arno Solin and Nicolas Gillis and Antonio Vergari , bibsource =

Reference 41

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Observation 2eaae6aa-6c2a-4e26-9eab-98bad60bf98a · outbound

This paper cites Tractable Regularization of Probabilistic Circuits , year =.

A Compositional Theory of Curvature in Probabilistic Circuits Tractable Regularization of Probabilistic Circuits , year =

Reference 42

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This paper cites Simplifying, regularizing and strengthening sum-product network structure learning , year =.

A Compositional Theory of Curvature in Probabilistic Circuits Simplifying, regularizing and strengthening sum-product network structure learning , year =

Reference 43

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This paper cites On the Relationship between Sum-Product Networks and Bayesian Networks , year =.

A Compositional Theory of Curvature in Probabilistic Circuits On the Relationship between Sum-Product Networks and Bayesian Networks , year =

Reference 44

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A Compositional Theory of Curvature in Probabilistic Circuits Random Sum-Product Networks:

Reference 45

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A Compositional Theory of Curvature in Probabilistic Circuits Group Fairness by Probabilistic Modeling with Latent Fair Decisions , year =

Reference 46

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A Compositional Theory of Curvature in Probabilistic Circuits Probabilistic sentential decision diagrams , year =

Reference 47

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This paper cites HyperSPNs: Compact and Expressive Probabilistic Circuits , year =.

A Compositional Theory of Curvature in Probabilistic Circuits HyperSPNs: Compact and Expressive Probabilistic Circuits , year =

Reference 48

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Observation f1ea1fcc-1031-42d2-ab99-13b6c4907f81 · outbound

This paper cites On the relationship between monotone and squared probabilistic circuits , year =.

A Compositional Theory of Curvature in Probabilistic Circuits On the relationship between monotone and squared probabilistic circuits , year =

Reference 49

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This paper cites Domingos , bibsource =.

A Compositional Theory of Curvature in Probabilistic Circuits Domingos , bibsource =

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:46:16.006624Z

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This paper cites IEEE Transactions on Pattern Analysis and Machine Intelligence , title =.

A Compositional Theory of Curvature in Probabilistic Circuits IEEE Transactions on Pattern Analysis and Machine Intelligence , title =

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:46:15.987968Z

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This paper cites Machine Learning , title =.

A Compositional Theory of Curvature in Probabilistic Circuits Machine Learning , title =

Reference 52

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Observation 4f043920-a0de-4371-b2b8-c36099f385c4 · outbound

This paper cites IEEE Transactions on Pattern Analysis and Machine Intelligence , title =.

A Compositional Theory of Curvature in Probabilistic Circuits IEEE Transactions on Pattern Analysis and Machine Intelligence , title =

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:46:15.952030Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7195a999-35ff-49e6-80b1-756b0c5ab79a · outbound

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

A Compositional Theory of Curvature in Probabilistic Circuits Advances in Neural Information Processing Systems , volume=

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:46:15.929757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation dee69488-78b5-4947-898c-581081f8f10f · outbound

This paper cites an unresolved cited work.

A Compositional Theory of Curvature in Probabilistic Circuits Unresolved cited work

Reference 55

Resolution: unresolved; raw_fallback, observed 2026-08-15T21:46:15.900683Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e47da1f6-3d42-46ef-92a6-ff13e4f4aec3 · outbound

This paper cites AAAI Conference on Artificial Intelligence , volume=.

A Compositional Theory of Curvature in Probabilistic Circuits AAAI Conference on Artificial Intelligence , volume=

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:46:15.883533Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ba8df711-583a-4d0a-b73b-3ffb18662dba · outbound

This paper cites Uncertainty in Artificial Intelligence , pages=.

A Compositional Theory of Curvature in Probabilistic Circuits Uncertainty in Artificial Intelligence , pages=

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:46:15.862581Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation fc3b8d89-fc1e-47c4-be54-1e0aa3a4e6bc · outbound

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

A Compositional Theory of Curvature in Probabilistic Circuits Advances in Neural Information Processing Systems , volume=

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:46:15.833690Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 57319cd9-cb20-441a-9579-5883a47fba47 · outbound

This paper cites Nalisnick and Danilo Jimenez Rezende and Shakir Mohamed and Balaji Lakshminarayanan , journal=.

A Compositional Theory of Curvature in Probabilistic Circuits Nalisnick and Danilo Jimenez Rezende and Shakir Mohamed and Balaji Lakshminarayanan , journal=

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:46:15.815101Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation d63adf40-1876-40f2-9304-f034587cf077 · outbound

This paper cites Stochastic Backpropagation and Approximate Inference in Deep Generative Models , year =.

A Compositional Theory of Curvature in Probabilistic Circuits Stochastic Backpropagation and Approximate Inference in Deep Generative Models , year =

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:46:15.796429Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation fbcb97b7-ffcc-404b-b233-ab17c49c9d5b · outbound

This paper cites Kingma and Max Welling , bibsource =.

A Compositional Theory of Curvature in Probabilistic Circuits Kingma and Max Welling , bibsource =

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:46:15.775670Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation cf02c09d-adb7-43a8-8b1d-88e5cdf6a0fa · outbound

This paper cites Goodfellow and Jean Pouget.

A Compositional Theory of Curvature in Probabilistic Circuits Goodfellow and Jean Pouget

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:46:15.740189Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 00a6f602-ebdc-4463-90f7-0734d0f02b22 · outbound

This paper cites Scaling Tractable Probabilistic Circuits:.

A Compositional Theory of Curvature in Probabilistic Circuits Scaling Tractable Probabilistic Circuits:

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:46:15.716299Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 794b04e5-f91a-48c3-8e56-22ad5ad5edb2 · outbound

This paper cites Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems, 2023 , title =.

A Compositional Theory of Curvature in Probabilistic Circuits Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems, 2023 , title =

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:46:15.695110Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b0416551-5e76-45e8-ad1c-41ec3d5b4137 · outbound

This paper cites SPFlow: An Easy and Extensible Library for Deep Probabilistic Learning Using Sum-Product Networks , year =.

A Compositional Theory of Curvature in Probabilistic Circuits SPFlow: An Easy and Extensible Library for Deep Probabilistic Learning Using Sum-Product Networks , year =

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:46:15.672889Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a7f45f43-d228-4a12-bbe5-ba254bcf6b5e · outbound

This paper cites Learning Arbitrary Sum-Product Network Leaves with Expectation-Maximization.

A Compositional Theory of Curvature in Probabilistic Circuits Learning Arbitrary Sum-Product Network Leaves with Expectation-Maximization

Reference 66

Resolution: metadata mismatch; local_arxiv, observed 2026-08-15T21:46:15.148952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 79597361-cd13-40e8-ac5c-ef19f2b2c51c · outbound

This paper cites Gordon , bibsource =.

A Compositional Theory of Curvature in Probabilistic Circuits Gordon , bibsource =

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:46:15.655693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 802307a7-8b1f-4068-a9fd-dfd009892f4b · outbound

This paper cites Domingos , bibsource =.

A Compositional Theory of Curvature in Probabilistic Circuits Domingos , bibsource =

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:46:15.636037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 0a606aca-58aa-45b6-9943-04b54c0196bf · outbound

This paper cites On the Sample Complexity of Learning Sum-Product Networks , year =.

A Compositional Theory of Curvature in Probabilistic Circuits On the Sample Complexity of Learning Sum-Product Networks , year =

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:46:15.617077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 67788376-ef22-4583-95e7-b90a9bfac2f6 · outbound

This paper cites Domingos , bibsource =.

A Compositional Theory of Curvature in Probabilistic Circuits Domingos , bibsource =

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:46:15.600858Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation d3f8ae36-cfeb-4f5c-8165-c87a67067fae · outbound

This paper cites Machine Learning , title =.

A Compositional Theory of Curvature in Probabilistic Circuits Machine Learning , title =

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:46:15.583120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 22960c84-5d8a-47b9-84e8-78a8ccb19ffa · outbound

This paper cites Journal of Statistical Mechanics: Theory and Experiment , title =.

A Compositional Theory of Curvature in Probabilistic Circuits Journal of Statistical Mechanics: Theory and Experiment , title =

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:46:15.566381Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e54035d6-3060-4d7a-85a1-aa26b27941c9 · outbound

This paper cites Probabilistic Flow Circuits: Towards Unified Deep Models for Tractable Probabilistic Inference , year =.

A Compositional Theory of Curvature in Probabilistic Circuits Probabilistic Flow Circuits: Towards Unified Deep Models for Tractable Probabilistic Inference , year =

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:46:15.548290Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 0530cc11-02ef-47b8-8f45-9d2639045183 · outbound

This paper cites Deep Tractable Probabilistic Models , year =.

A Compositional Theory of Curvature in Probabilistic Circuits Deep Tractable Probabilistic Models , year =

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:46:15.527315Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e2ca840b-33f1-4488-8fa3-91697946f0b1 · outbound

This paper cites Interventional Sum-Product Networks: Causal Inference with Tractable Probabilistic Models , year =.

A Compositional Theory of Curvature in Probabilistic Circuits Interventional Sum-Product Networks: Causal Inference with Tractable Probabilistic Models , year =

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:46:15.503645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9e66c637-53a1-4bae-bc83-e2b6209a126c · outbound

This paper cites Haas and Kristian Kersting and Sriraam Natarajan , booktitle =.

A Compositional Theory of Curvature in Probabilistic Circuits Haas and Kristian Kersting and Sriraam Natarajan , booktitle =

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:46:15.482423Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 1e5b01ed-fd1b-4d15-bb4a-27ff4abd92fb · outbound

This paper cites an unresolved cited work.

A Compositional Theory of Curvature in Probabilistic Circuits Unresolved cited work

Reference 77

Resolution: unresolved; raw_fallback, observed 2026-08-15T21:46:15.462696Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 0547ebef-d45a-40d9-b19c-bd8030157cab · outbound

This paper cites AAAI Conference on Artificial Intelligence , volume=.

A Compositional Theory of Curvature in Probabilistic Circuits AAAI Conference on Artificial Intelligence , volume=

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:46:15.445197Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation fcbd9fa3-741f-407b-b45b-750ba2215d4c · outbound

This paper cites Transactions on Machine Learning Research , issn=.

A Compositional Theory of Curvature in Probabilistic Circuits Transactions on Machine Learning Research , issn=

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:46:15.426912Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation fd098400-62e2-4e8c-87fc-0b31e50bf383 · outbound

This paper cites Chayes and Levent Sagun and Riccardo Zecchina , bibsource =.

A Compositional Theory of Curvature in Probabilistic Circuits Chayes and Levent Sagun and Riccardo Zecchina , bibsource =

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:46:15.404194Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3902f5b0-b93f-4dcc-8fc9-456f2429dacb · outbound

This paper cites 29th International Conference on Machine Learning, 2012 , title =.

A Compositional Theory of Curvature in Probabilistic Circuits 29th International Conference on Machine Learning, 2012 , title =

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:46:15.386120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7155ebc1-4d07-41fb-a5fd-5c3f348844a4 · outbound

This paper cites AAAI Conference on Artificial Intelligence, 2012 , title =.

A Compositional Theory of Curvature in Probabilistic Circuits AAAI Conference on Artificial Intelligence, 2012 , title =

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:46:15.367619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 2f0440f9-47a4-4f0b-bf11-73caec0ad5a6 · outbound

This paper cites Journal of Machine Learning Research , title =.

A Compositional Theory of Curvature in Probabilistic Circuits Journal of Machine Learning Research , title =

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:46:15.348186Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation d1b50e50-f14c-40ff-9434-6fec02a48383 · outbound

This paper cites AAAI Conference on Artificial Intelligence , volume=.

A Compositional Theory of Curvature in Probabilistic Circuits AAAI Conference on Artificial Intelligence , volume=

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:46:15.326959Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ba8c1a47-d423-4944-af00-8f5293a2738b · outbound

This paper cites AAAI Conference on Artificial Intelligence , volume=.

A Compositional Theory of Curvature in Probabilistic Circuits AAAI Conference on Artificial Intelligence , volume=

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:46:15.298298Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a8b4c1a4-9f6e-4423-a483-3d84d2a1a388 · outbound

This paper cites International Conference on Artificial Intelligence and Statistics , pages=.

A Compositional Theory of Curvature in Probabilistic Circuits International Conference on Artificial Intelligence and Statistics , pages=

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:46:15.276791Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 56f535dd-3956-425e-9545-0458a7da281e · outbound

This paper cites International Journal of Approximate Reasoning , volume=.

A Compositional Theory of Curvature in Probabilistic Circuits International Journal of Approximate Reasoning , volume=

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:46:15.256313Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 969c69b0-c3d4-46ec-a71d-cf30f43fda29 · outbound

This paper cites Tractable Sharpness-Aware Learning of Probabilistic Circuits.

A Compositional Theory of Curvature in Probabilistic Circuits Tractable Sharpness-Aware Learning of Probabilistic Circuits

Reference 88

Resolution: metadata mismatch; local_arxiv, observed 2026-08-15T21:46:15.117698Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 93acf0db-9cec-4795-90b0-226ad81adb8a · outbound

This paper cites International Conference on Artificial Intelligence and Statistics , pages=.

A Compositional Theory of Curvature in Probabilistic Circuits International Conference on Artificial Intelligence and Statistics , pages=

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:46:15.234171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 4d007c20-211c-4058-b8b1-77577ccc16cb · outbound

This paper cites 2026 , eprint=.

A Compositional Theory of Curvature in Probabilistic Circuits 2026 , eprint=

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:46:15.206378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 025c8b07-66fb-4053-ae8c-9df82c41b84b · outbound

This paper cites International Conference on Learning Representations , volume=.

A Compositional Theory of Curvature in Probabilistic Circuits International Conference on Learning Representations , volume=

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:46:15.188584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 5991d660-f043-4784-b712-45d94484797b · outbound

This paper cites Proceedings of the AAAI Conference on Artificial Intelligence , author=.

A Compositional Theory of Curvature in Probabilistic Circuits Proceedings of the AAAI Conference on Artificial Intelligence , author=

Reference 92

Resolution: verified exact; doi, observed 2026-08-15T21:46:15.079146Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3e2784de-a24c-469d-9f7d-c7d7b1fe383e · outbound

This paper cites ArXiv , year=.

A Compositional Theory of Curvature in Probabilistic Circuits ArXiv , year=

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:46:15.170383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers