Paper Citation Record · LEDGER

Density Ratio Estimation with Conditional Probability Paths

As of 10 August 2026, this Paper Citation Record lists 60 of 60 outbound references and 1 inbound Pith citation observation for arXiv:2502.02300.

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

pith.paper-citation-record.v1
2502.02300 v3

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measured 60 of 60 reference resolution

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Pith citing papers itemized under the disclosed page cap.

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Reference resolution

60 of 60 outbound references displayed

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External citation measurements

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Outbound references

Observation dec382e0-3167-4005-b255-16323085ce72 · outbound

This paper cites an unresolved cited work.

Density Ratio Estimation with Conditional Probability Paths Unresolved cited work

Reference 1

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Observation 4c15d3f9-5c09-4d20-b262-1f5f37f3cf1a · outbound

This paper cites Learning Theory from First Principles.

Density Ratio Estimation with Conditional Probability Paths Learning Theory from First Principles

Reference 2

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Observation 5b5af6ab-e67d-43e1-83e4-6f3d93f2c933 · outbound

This paper cites Target Score Matching.

Density Ratio Estimation with Conditional Probability Paths Target Score Matching

Reference 3

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Observation 8ac6465e-390a-40ce-bdd4-08f30b960b1e · outbound

This paper cites Accurate and conservative estimates of MRF log-likelihood using reverse annealing.

Density Ratio Estimation with Conditional Probability Paths Accurate and conservative estimates of MRF log-likelihood using reverse annealing

Reference 4

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Observation 51552647-db70-4ad0-bf9f-58b0576f6697 · outbound

This paper cites Optimizing the Noise in Self-Supervised Learning: from Importance Sampling to Noise-Contrastive Estimation.

Density Ratio Estimation with Conditional Probability Paths Optimizing the Noise in Self-Supervised Learning: from Importance Sampling to Noise-Contrastive Estimation

Reference 5

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This paper cites Provable benefits of annealing for estimating normalizing constants: Importance Sampling , Noise - Contrastive Estimation , and beyond.

Density Ratio Estimation with Conditional Probability Paths Provable benefits of annealing for estimating normalizing constants: Importance Sampling , Noise - Contrastive Estimation , and beyond

Reference 6

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Observation 4e7cb287-803c-4362-95ae-6b484b94293c · outbound

This paper cites The probability flow ODE is provably fast.

Density Ratio Estimation with Conditional Probability Paths The probability flow ODE is provably fast

Reference 7

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Observation bc6e0c2d-b13f-4102-bf81-3b4fdab2face · outbound

This paper cites On the importance of noise scheduling for diffusion models, 2023.

Density Ratio Estimation with Conditional Probability Paths On the importance of noise scheduling for diffusion models, 2023

Reference 8

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Observation 5605512c-fc3a-46e2-b04b-b51b5b68431f · outbound

This paper cites Density ratio estimation via infinitesimal classification.

Density Ratio Estimation with Conditional Probability Paths Density ratio estimation via infinitesimal classification

Reference 9

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Observation 216d9b31-2fac-4b57-abc1-1a286ed10786 · outbound

This paper cites Fast and Accurate Deep Network Learning by Exponential Linear Units ( ELUs ).

Density Ratio Estimation with Conditional Probability Paths Fast and Accurate Deep Network Learning by Exponential Linear Units ( ELUs )

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T12:44:18.384147Z

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Observation f9d2af6e-735c-432d-b306-810500e23309 · outbound

This paper cites W., and Doucet, A.

Density Ratio Estimation with Conditional Probability Paths W., and Doucet, A

Reference 11

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Density Ratio Estimation with Conditional Probability Paths Unresolved cited work

Reference 12

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Observation 2c174a94-7c17-4467-95e5-17aeefa9de63 · outbound

This paper cites B., Dieleman, S., Fergus, R., Sohl-Dickstein, J.

Density Ratio Estimation with Conditional Probability Paths B., Dieleman, S., Fergus, R., Sohl-Dickstein, J

Reference 13

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This paper cites Random fields and diffusion processes.

Density Ratio Estimation with Conditional Probability Paths Random fields and diffusion processes

Reference 14

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Observation 409236d1-789c-418e-8e2e-0663c21d3f5b · outbound

This paper cites P., Xu, Z., Dai, A.

Density Ratio Estimation with Conditional Probability Paths P., Xu, Z., Dai, A

Reference 15

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Density Ratio Estimation with Conditional Probability Paths Unresolved cited work

Reference 16

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Observation 61452be7-225a-4216-9b50-f91914a54086 · outbound

This paper cites Generative Adversarial Networks.

Density Ratio Estimation with Conditional Probability Paths Generative Adversarial Networks

Reference 17

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Observation bd3a763e-1fc2-48dd-a456-dc06e268c7b2 · outbound

This paper cites Provable Benefit of Annealed Langevin Monte Carlo for Non -log-concave Sampling.

Density Ratio Estimation with Conditional Probability Paths Provable Benefit of Annealed Langevin Monte Carlo for Non -log-concave Sampling

Reference 18

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Observation c64e9deb-6e1a-4f65-94bb-feee713e4bca · outbound

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Density Ratio Estimation with Conditional Probability Paths Unresolved cited work

Reference 19

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This paper cites Deep Residual Learning for Image Recognition.

Density Ratio Estimation with Conditional Probability Paths Deep Residual Learning for Image Recognition

Reference 20

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Density Ratio Estimation with Conditional Probability Paths Denoising Diffusion Probabilistic Models

Reference 21

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Observation ac4a7369-913b-4778-99ea-0ca5b42d867e · outbound

This paper cites Estimation of non-normalized statistical models by score matching.

Density Ratio Estimation with Conditional Probability Paths Estimation of non-normalized statistical models by score matching

Reference 22

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Observation 0b4783ee-55cc-44e7-b414-8ef96e57e472 · outbound

This paper cites High- Dimensional Density Ratio Estimation with Extensions to Approximate Likelihood Computation.

Density Ratio Estimation with Conditional Probability Paths High- Dimensional Density Ratio Estimation with Extensions to Approximate Likelihood Computation

Reference 23

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This paper cites P., and Mallat, S.

Density Ratio Estimation with Conditional Probability Paths P., and Mallat, S

Reference 24

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This paper cites An analytic theory of creativity in convolutional diffusion models.

Density Ratio Estimation with Conditional Probability Paths An analytic theory of creativity in convolutional diffusion models

Reference 25

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This paper cites Multi-task learning using uncertainty to weigh losses for scene geometry and semantics.

Density Ratio Estimation with Conditional Probability Paths Multi-task learning using uncertainty to weigh losses for scene geometry and semantics

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T12:44:18.282396Z

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Density Ratio Estimation with Conditional Probability Paths and Bondell, H

Reference 27

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Density Ratio Estimation with Conditional Probability Paths and Gao, R

Reference 28

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This paper cites MNIST handwritten digit database.

Density Ratio Estimation with Conditional Probability Paths MNIST handwritten digit database

Reference 29

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Density Ratio Estimation with Conditional Probability Paths P., and Risteski, A

Reference 30

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Density Ratio Estimation with Conditional Probability Paths Unresolved cited work

Reference 31

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Density Ratio Estimation with Conditional Probability Paths K., and Risteski, A

Reference 32

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This paper cites Minimizing f -divergences by interpolating velocity fields.

Density Ratio Estimation with Conditional Probability Paths Minimizing f -divergences by interpolating velocity fields

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T12:44:18.231275Z

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

Density Ratio Estimation with Conditional Probability Paths Flow Straight and Fast : Learning to Generate and Transfer Data with Rectified Flow

Reference 34

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Density Ratio Estimation with Conditional Probability Paths Autoregressive Score Matching

Reference 35

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Density Ratio Estimation with Conditional Probability Paths Annealed importance sampling

Reference 36

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Density Ratio Estimation with Conditional Probability Paths Unresolved cited work

Reference 37

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Density Ratio Estimation with Conditional Probability Paths Unresolved cited work

Reference 38

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Density Ratio Estimation with Conditional Probability Paths Unresolved cited work

Reference 39

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This paper cites An Overview of Multi-Task Learning in Deep Neural Networks.

Density Ratio Estimation with Conditional Probability Paths An Overview of Multi-Task Learning in Deep Neural Networks

Reference 40

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Reference 41

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Density Ratio Estimation with Conditional Probability Paths Unresolved cited work

Reference 42

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This paper cites Deep Unsupervised Learning using Nonequilibrium Thermodynamics.

Density Ratio Estimation with Conditional Probability Paths Deep Unsupervised Learning using Nonequilibrium Thermodynamics

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T12:44:18.163450Z

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Density Ratio Estimation with Conditional Probability Paths and Ermon, S

Reference 44

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Observation 630c184a-fac2-4e7d-a6a4-f7e1e1a7d6ea · outbound

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Density Ratio Estimation with Conditional Probability Paths Maximum Likelihood Training of Score - Based Diffusion Models

Reference 45

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Density Ratio Estimation with Conditional Probability Paths P., Kumar, A., Ermon, S., and Poole, B

Reference 46

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Reference 47

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This paper cites Density ratio estimation: A comprehensive review.

Density Ratio Estimation with Conditional Probability Paths Density ratio estimation: A comprehensive review

Reference 48

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Observation 18184af9-a852-4708-aa59-31cc0da5cc73 · outbound

This paper cites Fourier features let networks learn high frequency functions in low dimensional domains.

Density Ratio Estimation with Conditional Probability Paths Fourier features let networks learn high frequency functions in low dimensional domains

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T12:44:18.119714Z

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Observation 2463f796-ff35-41c2-b66a-07fa7b0a8a05 · outbound

This paper cites Improving and generalizing flow-based generative models with minibatch optimal transport.

Density Ratio Estimation with Conditional Probability Paths Improving and generalizing flow-based generative models with minibatch optimal transport

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T12:44:18.110674Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 7098b3dc-b63b-430a-9577-c2e980dd5ff1 · outbound

This paper cites Y., Malkin, N., Fatras, K., Atanackovic, L., Zhang, Y., Huguet, G., Wolf, G., and Bengio, Y.

Density Ratio Estimation with Conditional Probability Paths Y., Malkin, N., Fatras, K., Atanackovic, L., Zhang, Y., Huguet, G., Wolf, G., and Bengio, Y

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T12:44:18.102023Z

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Observation 63d73062-5ee0-4939-b7ff-69733db2bf1d · outbound

This paper cites Asymptotic Statistics.

Density Ratio Estimation with Conditional Probability Paths Asymptotic Statistics

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T12:44:18.093382Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 3ff6d7aa-eed3-4f4b-8865-afe2f2d0bcea · outbound

This paper cites A connection between score matching and denoising autoencoders.

Density Ratio Estimation with Conditional Probability Paths A connection between score matching and denoising autoencoders

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T12:44:18.084786Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 7cf49b98-7a11-4bf1-8155-85ff233e7ef5 · outbound

This paper cites E., Haberland, M., Reddy, T., Cournapeau, D., Burovski, E., Peterson, P., Weckesser, W., Bright, J., van der Walt, S.

Density Ratio Estimation with Conditional Probability Paths E., Haberland, M., Reddy, T., Cournapeau, D., Burovski, E., Peterson, P., Weckesser, W., Bright, J., van der Walt, S

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T12:44:18.075392Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 77861b38-b9a1-474b-a991-263204d8c947 · outbound

This paper cites Learning Calibrated Uncertainties for Domain Shift : A Distributionally Robust Learning Approach.

Density Ratio Estimation with Conditional Probability Paths Learning Calibrated Uncertainties for Domain Shift : A Distributionally Robust Learning Approach

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T12:44:18.065869Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 192dafa1-9d5f-45ab-8697-0d52fc18d660 · outbound

This paper cites J., Wang, L., Ying, Q., Liu, S., and Kolar, M.

Density Ratio Estimation with Conditional Probability Paths J., Wang, L., Ying, Q., Liu, S., and Kolar, M

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T12:44:18.057324Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 0060f075-d29b-4ed5-9e4c-33fab714dd99 · outbound

This paper cites Annealing Flow Generative Models Towards Sampling High-Dimensional and Multi-Modal Distributions.

Density Ratio Estimation with Conditional Probability Paths Annealing Flow Generative Models Towards Sampling High-Dimensional and Multi-Modal Distributions

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-09T12:44:17.955869Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 299c7b62-5e6c-4f33-8078-c6c8a6a644cb · outbound

This paper cites Computing high-dimensional optimal transport by flow neural networks.

Density Ratio Estimation with Conditional Probability Paths Computing high-dimensional optimal transport by flow neural networks

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T12:44:18.048808Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation abf92892-87c3-4d7b-bb01-16efaf6ed98b · outbound

This paper cites Classification Diffusion Models : Revitalizing Density Ratio Estimation.

Density Ratio Estimation with Conditional Probability Paths Classification Diffusion Models : Revitalizing Density Ratio Estimation

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T12:44:18.040055Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 0415a3b1-fc22-440d-afd0-4346d760dfa9 · outbound

This paper cites and Michaeli, T.

Density Ratio Estimation with Conditional Probability Paths and Michaeli, T

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T12:44:18.030365Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Pith citing papers

Observation 3cc51676-e641-4c65-86af-d3d63f08240a · inbound

Marginal Girsanov Reweighting: Stable Variance Reduction for Long-Timescale Dynamics from Biased Simulation cites this paper.

Marginal Girsanov Reweighting: Stable Variance Reduction for Long-Timescale Dynamics from Biased Simulation Density Ratio Estimation with Conditional Probability Paths

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-18T12:06:20.847161Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.