Paper Citation Record · LEDGER

Comparing Normalizing Flows with Kernel Density Estimation in Estimating Risk of Automated Driving Systems

As of 17 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2507.22429.

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

pith.paper-citation-record.v1
2507.22429 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T11:45:54.927475Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

35 of 35 outbound references displayed

verified exact2
verified fuzzy27
unresolved6
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a8503d3c-5000-42f1-ae85-f67e08633fe0 · outbound

This paper cites Advancements, prospects, and impacts of automated driving systems,.

Comparing Normalizing Flows with Kernel Density Estimation in Estimating Risk of Automated Driving Systems Advancements, prospects, and impacts of automated driving systems,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:45:57.349326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 4020f3db-faaa-4052-a2df-0389e9277ece · outbound

This paper cites Driving to safety: How many miles of driving would it take to demonstrate autonomous vehicle reliability?.

Comparing Normalizing Flows with Kernel Density Estimation in Estimating Risk of Automated Driving Systems Driving to safety: How many miles of driving would it take to demonstrate autonomous vehicle reliability?

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T11:45:52.613068Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5c330461-083e-4601-8b97-36d29033b8fd · outbound

This paper cites Survey on scenario-based safety assessment of automated vehicles,.

Comparing Normalizing Flows with Kernel Density Estimation in Estimating Risk of Automated Driving Systems Survey on scenario-based safety assessment of automated vehicles,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:45:57.332647Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 903e0dcb-c196-4503-824d-6c3c8b71cb8c · outbound

This paper cites Scenario-based safety assessment of automated driving systems,.

Comparing Normalizing Flows with Kernel Density Estimation in Estimating Risk of Automated Driving Systems Scenario-based safety assessment of automated driving systems,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:45:57.323237Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 13a6918a-c94d-4a1c-b31f-d18c3c97f490 · outbound

This paper cites Remarks on some nonparametric estimates of a density function,.

Comparing Normalizing Flows with Kernel Density Estimation in Estimating Risk of Automated Driving Systems Remarks on some nonparametric estimates of a density function,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:45:57.313456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 5c9cb1f7-1c0b-44ad-ae93-cf9c1e711b12 · outbound

This paper cites On estimation of a probability density function and mode,.

Comparing Normalizing Flows with Kernel Density Estimation in Estimating Risk of Automated Driving Systems On estimation of a probability density function and mode,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:45:57.304119Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1ed2fcc1-ea51-4e3e-b4e0-e61d62cd356f · outbound

This paper cites Risk quantification for automated driving systems in real-world driving scenarios,.

Comparing Normalizing Flows with Kernel Density Estimation in Estimating Risk of Automated Driving Systems Risk quantification for automated driving systems in real-world driving scenarios,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:45:57.294808Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b2ca4e4e-9888-4216-8e5b-f41150f7220c · outbound

This paper cites How certain are we that our automated driving system is safe?.

Comparing Normalizing Flows with Kernel Density Estimation in Estimating Risk of Automated Driving Systems How certain are we that our automated driving system is safe?

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:45:57.285694Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a3aeb94d-4775-48af-9b22-63e78aa55d9a · outbound

This paper cites Normalizing flows for probabilistic modeling and inference,.

Comparing Normalizing Flows with Kernel Density Estimation in Estimating Risk of Automated Driving Systems Normalizing flows for probabilistic modeling and inference,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:45:57.276262Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8066befd-085c-4684-ad0b-e6daca550030 · outbound

This paper cites A taxonomy of validation strategies to ensure the safe operation of highly automated vehicles,.

Comparing Normalizing Flows with Kernel Density Estimation in Estimating Risk of Automated Driving Systems A taxonomy of validation strategies to ensure the safe operation of highly automated vehicles,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:45:57.266381Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 69b73839-218a-4a4b-bfe7-24f6ef06a452 · outbound

This paper cites A survey on data-driven scenario generation for automated vehicle testing,.

Comparing Normalizing Flows with Kernel Density Estimation in Estimating Risk of Automated Driving Systems A survey on data-driven scenario generation for automated vehicle testing,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:45:57.256506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 53999fad-0099-44cf-9e75-b756fbeb3bdc · outbound

This paper cites 1001 ways of scenario generation for testing of self-driving cars: A survey,.

Comparing Normalizing Flows with Kernel Density Estimation in Estimating Risk of Automated Driving Systems 1001 ways of scenario generation for testing of self-driving cars: A survey,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:45:57.247347Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 679a474e-2efa-4769-b380-52970c48ed30 · outbound

This paper cites A survey on safety-critical driving scenario generation — a methodological perspec- tive,.

Comparing Normalizing Flows with Kernel Density Estimation in Estimating Risk of Automated Driving Systems A survey on safety-critical driving scenario generation — a methodological perspec- tive,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:45:57.237950Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9e3f2833-b2db-455d-a3b0-41c2eed7e5da · outbound

This paper cites A review on scenario generation for testing autonomous vehicles,.

Comparing Normalizing Flows with Kernel Density Estimation in Estimating Risk of Automated Driving Systems A review on scenario generation for testing autonomous vehicles,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:45:57.228639Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation dbeb1932-4cbd-42e8-8d77-051c2d4878c3 · outbound

This paper cites A comprehensive literature review on artificial dataset generation for repositioning challenges in shared electric automated and connected mobility,.

Comparing Normalizing Flows with Kernel Density Estimation in Estimating Risk of Automated Driving Systems A comprehensive literature review on artificial dataset generation for repositioning challenges in shared electric automated and connected mobility,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:45:57.219060Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 898c197b-3f35-453f-b616-8017636f7023 · outbound

This paper cites Road Vehicles – Functional Safety,.

Comparing Normalizing Flows with Kernel Density Estimation in Estimating Risk of Automated Driving Systems Road Vehicles – Functional Safety,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:45:57.209579Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f0d3e93c-94ff-4a33-9d0e-c3adf5da7613 · outbound

This paper cites Comparative assessment of safety indicators for vehicle trajectories on highways,.

Comparing Normalizing Flows with Kernel Density Estimation in Estimating Risk of Automated Driving Systems Comparative assessment of safety indicators for vehicle trajectories on highways,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:45:57.200347Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 28007584-ddb9-4808-a6c2-2d73810b2e38 · outbound

This paper cites Variational inference with normaliz- ing flows,.

Comparing Normalizing Flows with Kernel Density Estimation in Estimating Risk of Automated Driving Systems Variational inference with normaliz- ing flows,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:45:57.191382Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8af4e25d-7452-4a38-98a5-bc894fd8b94d · outbound

This paper cites Masked autoregressive flow for density estimation,.

Comparing Normalizing Flows with Kernel Density Estimation in Estimating Risk of Automated Driving Systems Masked autoregressive flow for density estimation,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:45:57.182074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 57dcbbd6-fae9-4e08-ab84-b38025d4a596 · outbound

This paper cites Identity mappings in deep residual networks,.

Comparing Normalizing Flows with Kernel Density Estimation in Estimating Risk of Automated Driving Systems Identity mappings in deep residual networks,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:45:57.172800Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f99e6a3d-6c7f-41ec-bc7a-5d8003b8f7bf · outbound

This paper cites How does batch normalization help optimization?.

Comparing Normalizing Flows with Kernel Density Estimation in Estimating Risk of Automated Driving Systems How does batch normalization help optimization?

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:45:57.162666Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1904e9f2-7ade-45dc-a9aa-2e5c068b879a · outbound

This paper cites NICE: Non-linear Independent Components Estimation.

Comparing Normalizing Flows with Kernel Density Estimation in Estimating Risk of Automated Driving Systems NICE: Non-linear Independent Components Estimation

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T11:45:54.026437Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c6c76e87-53f8-4662-8d61-3f2e164b83d9 · outbound

This paper cites Adam: A method for stochastic optimization,.

Comparing Normalizing Flows with Kernel Density Estimation in Estimating Risk of Automated Driving Systems Adam: A method for stochastic optimization,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:45:57.148478Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c041b3ca-2913-4963-aac0-124f2e79b4f2 · outbound

This paper cites Bandwidth selection in kernel density estimation: A review,.

Comparing Normalizing Flows with Kernel Density Estimation in Estimating Risk of Automated Driving Systems Bandwidth selection in kernel density estimation: A review,

Reference 24

Resolution: verified exact; raw_fallback, observed 2026-08-06T11:45:55.434432Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 70368351-6a49-4844-bfcb-218c64b181ea · outbound

This paper cites an unresolved cited work.

Comparing Normalizing Flows with Kernel Density Estimation in Estimating Risk of Automated Driving Systems Unresolved cited work

Reference 25

Resolution: unresolved; raw_fallback, observed 2026-08-06T11:45:56.964536Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1df3a12f-8764-4355-990f-03019bd16f71 · outbound

This paper cites Driver models for the definition of safety requirements of automated vehicles in international regulations. applica- tion to motorway driving conditions,.

Comparing Normalizing Flows with Kernel Density Estimation in Estimating Risk of Automated Driving Systems Driver models for the definition of safety requirements of automated vehicles in international regulations. applica- tion to motorway driving conditions,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:45:56.800398Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation de8f63d2-7dc3-4b1b-b4cc-3b53c5c6fdd8 · outbound

This paper cites Fuzzy surrogate safety metrics for real-time assessment of rear-end collision risk. a study based on empirical observations,.

Comparing Normalizing Flows with Kernel Density Estimation in Estimating Risk of Automated Driving Systems Fuzzy surrogate safety metrics for real-time assessment of rear-end collision risk. a study based on empirical observations,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:45:56.641752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e62a4154-80b6-4a10-9982-b3152e5aff1b · outbound

This paper cites The highD dataset: A drone dataset of naturalistic vehicle trajectories on German highways for validation of highly automated driving systems,.

Comparing Normalizing Flows with Kernel Density Estimation in Estimating Risk of Automated Driving Systems The highD dataset: A drone dataset of naturalistic vehicle trajectories on German highways for validation of highly automated driving systems,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:45:56.449607Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c8b8b91d-df91-4d74-bf4f-1d7a9e2fe11e · outbound

This paper cites Real-world scenario mining for the assessment of automated vehicles,.

Comparing Normalizing Flows with Kernel Density Estimation in Estimating Risk of Automated Driving Systems Real-world scenario mining for the assessment of automated vehicles,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:45:56.235266Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9436c7d4-b344-4bef-9c69-29a2499fbf87 · outbound

This paper cites Scenario-based assessment of automated driving systems: How (not) to parameterize scenarios?.

Comparing Normalizing Flows with Kernel Density Estimation in Estimating Risk of Automated Driving Systems Scenario-based assessment of automated driving systems: How (not) to parameterize scenarios?

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:45:56.033533Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 00ddcb4d-bddd-4b7f-8727-097ad0395bd6 · outbound

This paper cites Flexible Tails for Normalizing Flows.

Comparing Normalizing Flows with Kernel Density Estimation in Estimating Risk of Automated Driving Systems Flexible Tails for Normalizing Flows

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-06T11:45:54.681056Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 15d72625-7172-42c1-8516-baf681a921da · outbound

This paper cites Tail density estimation for exploratory data analysis using kernel methods,.

Comparing Normalizing Flows with Kernel Density Estimation in Estimating Risk of Automated Driving Systems Tail density estimation for exploratory data analysis using kernel methods,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:45:55.823229Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 643187be-6dc4-4e4f-adc9-4499c264bee1 · outbound

This paper cites an unresolved cited work.

Comparing Normalizing Flows with Kernel Density Estimation in Estimating Risk of Automated Driving Systems Unresolved cited work

Reference 33

Resolution: unresolved; raw_fallback, observed 2026-08-06T11:45:55.639370Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8d69085d-bb82-4a1b-8e36-2fbc9f2a42ce · outbound

This paper cites Tutorial on Variational Autoencoders.

Comparing Normalizing Flows with Kernel Density Estimation in Estimating Risk of Automated Driving Systems Tutorial on Variational Autoencoders

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-06T11:45:54.847405Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f16d014b-3b34-4b60-ad67-cd1cc4e2902f · outbound

This paper cites Diffusion Density Estimators.

Comparing Normalizing Flows with Kernel Density Estimation in Estimating Risk of Automated Driving Systems Diffusion Density Estimators

Reference 35

Resolution: verified exact; local_arxiv, observed 2026-08-06T11:45:55.149162Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Pith citing papers

No inbound Pith citation observations are available.