A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models | Paper Citation Record

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This paper cites Denoising Diffusion Probabilistic Models.

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Denoising Diffusion Probabilistic Models

Reference 1

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This paper cites Score-Based Generative Modeling through Stochastic Differential Equations.

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Score-Based Generative Modeling through Stochastic Differential Equations

Reference 2

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This paper cites Flow Matching for Generative Modeling.

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Flow Matching for Generative Modeling

Reference 3

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

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Journal of Machine Learning Research , volume =

Reference 4

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This paper cites Neural Computation , volume =.

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Neural Computation , volume =

Reference 5

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

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Advances in Neural Information Processing Systems , year =

Reference 6

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This paper cites Stochastic Processes and their Applications , volume =.

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Stochastic Processes and their Applications , volume =

Reference 7

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Observation c18d4f9d-9351-4395-ac6d-cdf56954c512 · outbound

This paper cites Diffusion Schr.

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Diffusion Schr

Reference 8

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Observation 5080e9dd-75ad-49b7-bad7-5a9b110ecd50 · outbound

This paper cites International Conference on Machine Learning , year =.

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models International Conference on Machine Learning , year =

Reference 9

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This paper cites Improved Denoising Diffusion Probabilistic Models.

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Improved Denoising Diffusion Probabilistic Models

Reference 10

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Observation 47ca6f19-3226-482a-83d7-e4f42a6fa12a · outbound

This paper cites FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative Models.

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative Models

Reference 11

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Observation fb6804e7-716c-4142-86cd-052f8aece520 · outbound

This paper cites Sliced Score Matching: A Scalable Approach to Density and Score Estimation.

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Sliced Score Matching: A Scalable Approach to Density and Score Estimation

Reference 12

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This paper cites Improved Techniques for Training Score-Based Generative Models.

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Improved Techniques for Training Score-Based Generative Models

Reference 13

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This paper cites Denoising Diffusion Implicit Models.

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Denoising Diffusion Implicit Models

Reference 14

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This paper cites Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow.

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow

Reference 15

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This paper cites Elucidating the Design Space of Diffusion-Based Generative Models.

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Elucidating the Design Space of Diffusion-Based Generative Models

Reference 16

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This paper cites Auto-Encoding Variational Bayes.

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Auto-Encoding Variational Bayes

Reference 17

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

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Stochastic Backpropagation and Approximate Inference in Deep Generative Models

Reference 18

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

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Advances in Neural Information Processing Systems , year =

Reference 19

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

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models International Conference on Learning Representations , year =

Reference 20

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This paper cites Density Estimation using Real.

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Density Estimation using Real

Reference 21

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This paper cites Towards Principled Methods for Training Generative Adversarial Networks.

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Towards Principled Methods for Training Generative Adversarial Networks

Reference 22

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This paper cites Which Training Methods for.

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Which Training Methods for

Reference 23

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This paper cites Improved Techniques for Training.

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Improved Techniques for Training

Reference 24

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This paper cites 2016 , url =.

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models 2016 , url =

Reference 25

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

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models International Conference on Learning Representations , year=

Reference 26

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

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models International Conference on Machine Learning , pages=

Reference 27

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This paper cites Variational Diffusion Models.

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Variational Diffusion Models

Reference 28

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

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Journal of Machine Learning Research , volume =

Reference 29

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This paper cites Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence , series =.

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence , series =

Reference 30

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

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Advances in Neural Information Processing Systems , volume =

Reference 31

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A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Medical Image Analysis , volume =

Reference 32

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

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Advances in Neural Information Processing Systems , volume =

Reference 33

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A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models International Conference on Learning Representations , year =

Reference 34

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This paper cites A Survey of the Schr.

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models A Survey of the Schr

Reference 35

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A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Cold Diffusion: Inverting Arbitrary Image Transforms Without Noise

Reference 36

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This paper cites Stochastic Interpolants: A Unifying Framework for Flows and Diffusions.

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Stochastic Interpolants: A Unifying Framework for Flows and Diffusions

Reference 37

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A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Bayesian Flow Networks

Reference 38

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A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Consistency Models

Reference 39

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A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Consistency Trajectory Models: Learning Probability Flow ODE Trajectory of Diffusion

Reference 40

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This paper cites Discrete Diffusion Modeling by Estimating the Ratios of the Data Distribution.

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Discrete Diffusion Modeling by Estimating the Ratios of the Data Distribution

Reference 41

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This paper cites arXiv preprint arXiv:2512.04985 , year=.

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models arXiv preprint arXiv:2512.04985 , year=

Reference 42

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This paper cites Score-based con- strained generative modeling via langevin diffusions with boundary conditions.

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Score-based con- strained generative modeling via langevin diffusions with boundary conditions

Reference 43

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

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Journal of Machine Learning Research , volume =

Reference 44

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

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models International Conference on Learning Representations , year =

Reference 45

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This paper cites Proceedings of the 41st International Conference on Machine Learning , series =.

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Proceedings of the 41st International Conference on Machine Learning , series =

Reference 46

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This paper cites Flow Matching Guide and Code.

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Flow Matching Guide and Code

Reference 47

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Observation e6e54130-cdc9-4fdb-ba08-7ba32b86a0f4 · outbound

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

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Transactions on Machine Learning Research , year =

Reference 48

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This paper cites Proceedings of the 42nd International Conference on Machine Learning , series =.

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Proceedings of the 42nd International Conference on Machine Learning , series =

Reference 49

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

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Advances in Neural Information Processing Systems , year =

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T17:27:30.929889Z

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Observation 1afee7ff-2ab3-4419-b1ce-154f7cf58aff · outbound

This paper cites Unifying Bayesian Flow Networks and Diffusion Models through Stochastic Differential Equations.

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Unifying Bayesian Flow Networks and Diffusion Models through Stochastic Differential Equations

Reference 51

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A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Exploring Diffusion and Flow Matching Under Generator Matching

Reference 52

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

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models International Conference on Learning Representations , year =

Reference 53

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A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Theoretical Guarantees in

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T17:27:30.978085Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models International Conference on Learning Representations , year =

Reference 55

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

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models International Conference on Learning Representations , year =

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T17:27:31.020853Z

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

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models International Conference on Learning Representations , year =

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T17:27:30.912884Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation f0637e35-e49c-4c15-8dee-a3b7aac6837c · outbound

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

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models International Conference on Learning Representations , year =

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T17:27:31.314642Z

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

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Advances in Neural Information Processing Systems , volume =

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T17:27:31.116400Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 23b2e4ba-74c5-4c87-97ac-35ad9e4567eb · outbound

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

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Advances in Neural Information Processing Systems , volume =

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T17:27:30.959977Z

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

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Proceedings of the 40th International Conference on Machine Learning , series =

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T17:27:30.947259Z

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

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models International Conference on Learning Representations , year =

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T17:27:30.943215Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 38e660fb-d1a0-4f1a-a385-1c20e9da115a · outbound

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

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Advances in Neural Information Processing Systems , volume =

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T17:27:31.052713Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Advances in Neural Information Processing Systems , volume =

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T17:27:30.866064Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Proceedings of The 27th International Conference on Artificial Intelligence and Statistics , series =

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T17:27:31.228519Z

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Observation 22d7150a-5c40-43ef-86da-27d5306ef432 · outbound

This paper cites Proceedings of the 42nd International Conference on Machine Learning , series =.

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Proceedings of the 42nd International Conference on Machine Learning , series =

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T17:27:31.176454Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation cab7f4a0-fe2b-4dc5-9ac0-407fa29a7b21 · outbound

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

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Proceedings of the 40th International Conference on Machine Learning , series =

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T17:27:31.075569Z

Source-reported events for the cited work

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Observation 4690093c-9ce9-4828-bdaa-aa693afa5f6f · outbound

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

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Proceedings of the 40th International Conference on Machine Learning , series =

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T17:27:31.286391Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 9bc1f118-22ed-4e8d-99a4-3a3a467e3093 · outbound

This paper cites Proceedings of The 27th International Conference on Artificial Intelligence and Statistics , series =.

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Proceedings of The 27th International Conference on Artificial Intelligence and Statistics , series =

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T17:27:31.137515Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 89f39965-6bb3-4536-a9b1-5e803709bf54 · outbound

This paper cites Proceedings of the 41st International Conference on Machine Learning , series =.

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Proceedings of the 41st International Conference on Machine Learning , series =

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T17:27:31.163536Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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This paper cites Proceedings of the 41st International Conference on Machine Learning , series =.

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Proceedings of the 41st International Conference on Machine Learning , series =

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T17:27:31.132933Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 6217b636-a2e9-4364-849e-51f9f30df3f6 · outbound

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

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Advances in Neural Information Processing Systems , volume =

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T17:27:31.256345Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 24bbb6e5-76ec-40fc-be9a-fe10e2cae327 · outbound

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

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Advances in Neural Information Processing Systems , volume =

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T17:27:31.124676Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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This paper cites Proceedings of the 42nd International Conference on Machine Learning , series =.

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Proceedings of the 42nd International Conference on Machine Learning , series =

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T17:27:31.155250Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 0a32c9e7-c27c-4f14-93c1-7bcc20cc5730 · outbound

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

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Advances in Neural Information Processing Systems , volume =

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T17:27:31.141745Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation cd036c7b-5ce1-4ac2-91dc-7e776d4438e5 · outbound

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

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Advances in Neural Information Processing Systems , volume =

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T17:27:31.242940Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Advances in Neural Information Processing Systems , volume =

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T17:27:31.268028Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Advances in Neural Information Processing Systems , volume =

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T17:27:31.212224Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 098572c0-ec76-4940-804e-1f6b1c0c4587 · outbound

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

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Advances in Neural Information Processing Systems , volume =

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T17:27:31.235243Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Advances in Neural Information Processing Systems , volume =

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T17:27:31.250485Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Advances in Neural Information Processing Systems , volume =

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T17:27:31.262333Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Advances in Neural Information Processing Systems , volume =

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T17:27:31.300017Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 0faf1ecf-a35e-4d0a-83bf-646d0fb357fc · outbound

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

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Advances in Neural Information Processing Systems , volume =

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T17:27:31.108953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation e35343fe-89dc-43c3-936a-1650d930f005 · outbound

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

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Advances in Neural Information Processing Systems , volume =

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T17:27:31.198205Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 04433218-8aa2-4708-b666-270a5eaff5b3 · outbound

This paper cites Proceedings of the 36th International Conference on Machine Learning , series =.

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Proceedings of the 36th International Conference on Machine Learning , series =

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T17:27:30.969591Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation a8887fc7-b10c-4105-95c9-1940858d687e · outbound

This paper cites Proceedings of the 37th International Conference on Machine Learning , series =.

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Proceedings of the 37th International Conference on Machine Learning , series =

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T17:27:31.034737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 5a1fd826-f9e0-4673-b329-3bec67cad54c · outbound

This paper cites Proceedings of the 39th International Conference on Machine Learning , series =.

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Proceedings of the 39th International Conference on Machine Learning , series =

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T17:27:31.026337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Proceedings of The 26th International Conference on Artificial Intelligence and Statistics , series =

Reference 88

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Observation 50e62724-310d-4a1a-82f6-553c263913c5 · outbound

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

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Proceedings of the 40th International Conference on Machine Learning , series =

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T17:27:31.000814Z

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A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Advances in Neural Information Processing Systems , volume =

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T17:27:31.219911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 808c26de-fb40-4f8a-bf4d-6ed86d454b89 · outbound

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

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Advances in Neural Information Processing Systems , volume =

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T17:27:31.180823Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 47b7fa54-294b-4dd0-b8f3-9170389cb176 · outbound

This paper cites Proceedings of the 41st International Conference on Machine Learning , series =.

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Proceedings of the 41st International Conference on Machine Learning , series =

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T17:27:31.191488Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 1a69bd02-ae96-4b5d-82f4-a2a982a57897 · outbound

This paper cites Proceedings of the 41st International Conference on Machine Learning , series =.

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Proceedings of the 41st International Conference on Machine Learning , series =

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T17:27:31.206217Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 56eeceba-c3bd-46d7-9d99-f584f424887c · outbound

This paper cites Proceedings of the 42nd International Conference on Machine Learning , series =.

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Proceedings of the 42nd International Conference on Machine Learning , series =

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T17:27:31.082448Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 7fcf95a4-5b05-48c6-9702-a0bd2e91c6e7 · outbound

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

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models International Conference on Learning Representations , year =

Reference 95

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T17:27:30.902603Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation a5ba2ff6-b67d-4816-94b8-69c72afe1bae · outbound

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

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , pages =

Reference 96

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T17:27:30.877791Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 3fc3d8b9-acde-43b5-9108-2e5ff97fa831 · outbound

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

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Advances in Neural Information Processing Systems , volume =

Reference 97

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T17:27:31.167932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 7f71f71f-b06f-4846-aa4a-889e8a1caf34 · outbound

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

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Advances in Neural Information Processing Systems , volume =

Reference 98

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T17:27:30.983523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 78549153-fd41-492f-b66f-ae4371af2587 · outbound

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

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Advances in Neural Information Processing Systems , volume =

Reference 99

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T17:27:30.861253Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation e2b52a3f-e451-4980-a36c-956e8ec8bac1 · outbound

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

A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision , pages =

Reference 100

Resolution: verified fuzzy; raw_fallback, observed 2026-05-14T17:27:31.307219Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers