Paper Citation Record · LEDGER

U-Net Training with Instance-Layer Normalization

As of 16 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 0 inbound Pith citation observations for arXiv:1908.08466.

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

pith.paper-citation-record.v1
1908.08466 v2

Coverage vector

measured 18 of 18 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T11:58:44.934385Z

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+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

18 of 18 outbound references displayed

verified exact0
verified fuzzy13
unresolved4
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 40d71601-3933-4c96-82f8-25a0549cf871 · outbound

This paper cites Stat 1050, 21 (2016).

U-Net Training with Instance-Layer Normalization Stat 1050, 21 (2016)

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:58:45.394478Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 7739871e-8b63-4a79-8134-b33db3f5a4a7 · outbound

This paper cites In: NeurIPS.

U-Net Training with Instance-Layer Normalization In: NeurIPS

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:58:45.373448Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 7d89fa83-2cdf-4098-bacb-d104b8586087 · outbound

This paper cites In: NeurIPS.

U-Net Training with Instance-Layer Normalization In: NeurIPS

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:58:45.355525Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 3b3dfc89-921a-48bf-a9ae-bbeeb3b183b6 · outbound

This paper cites In: ICML.

U-Net Training with Instance-Layer Normalization In: ICML

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:58:45.336393Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 8e5d634f-03c5-4103-8c96-f85d2abfc705 · outbound

This paper cites In: NeurIPS.

U-Net Training with Instance-Layer Normalization In: NeurIPS

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:58:45.314312Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 934d857d-1c6a-4a5d-819e-99aff7beddb8 · outbound

This paper cites The MIDAS Journal- Cardiac MR Left Ventricle Segmentation Challenge 49 (2009).

U-Net Training with Instance-Layer Normalization The MIDAS Journal- Cardiac MR Left Ventricle Segmentation Challenge 49 (2009)

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:58:45.293789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation c6924827-93aa-460d-a9a3-bc74aad8e1ce · outbound

This paper cites In: MICCAI.

U-Net Training with Instance-Layer Normalization In: MICCAI

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-14T11:58:44.856631Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f699517b-fc61-47d7-99c6-3a611d272c95 · outbound

This paper cites In: NeurIPS.

U-Net Training with Instance-Layer Normalization In: NeurIPS

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:58:45.244843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 121d792f-16af-4ca4-84e8-b0b85a750b64 · outbound

This paper cites an unresolved cited work.

U-Net Training with Instance-Layer Normalization Unresolved cited work

Reference 9

Resolution: unresolved; raw_fallback, observed 2026-08-14T11:58:45.225412Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 5c550b1c-41c4-4ae5-81d1-b8a9ea9cb3f6 · outbound

This paper cites Instance Normalization: The Missing Ingredient for Fast Stylization.

U-Net Training with Instance-Layer Normalization Instance Normalization: The Missing Ingredient for Fast Stylization

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-14T11:58:44.876789Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c9213a79-0a28-465a-833c-b0b53d12f208 · outbound

This paper cites Batch Kalman Normalization: Towards Training Deep Neural Networks with Micro-Batches.

U-Net Training with Instance-Layer Normalization Batch Kalman Normalization: Towards Training Deep Neural Networks with Micro-Batches

Reference 11

Resolution: metadata mismatch; local_arxiv, observed 2026-08-14T11:58:45.032533Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation d17aa107-f62d-4ba8-a14d-255c9428f7b7 · outbound

This paper cites In: ECCV.

U-Net Training with Instance-Layer Normalization In: ECCV

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:58:45.202125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation b9c2a190-447b-4d0d-8a81-6e36caddaaef · outbound

This paper cites In: NeurIPS.

U-Net Training with Instance-Layer Normalization In: NeurIPS

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:58:45.172618Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 4f27879a-270c-4b87-814f-3a2f7b20a36e · outbound

This paper cites IEEE RAL 3(2), 1314–1321 (2018).

U-Net Training with Instance-Layer Normalization IEEE RAL 3(2), 1314–1321 (2018)

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:58:45.146051Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 7822c7b0-5e71-4013-b825-ed93755e6546 · outbound

This paper cites In: 2018 IEEE/RSJ IROS.

U-Net Training with Instance-Layer Normalization In: 2018 IEEE/RSJ IROS

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:58:45.116746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 5e638385-ab59-4e10-b3d2-1277fa4c0c0b · outbound

This paper cites IEEE RAL (2019).

U-Net Training with Instance-Layer Normalization IEEE RAL (2019)

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:58:45.096396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 628516ff-f062-4287-9cff-d0230d830973 · outbound

This paper cites MedIA 44, 86–97 (2018).

U-Net Training with Instance-Layer Normalization MedIA 44, 86–97 (2018)

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:58:45.078954Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation f1fc6dc6-4a77-40f6-93fd-0b9bfdcf9a59 · outbound

This paper cites ACNN: a Full Resolution DCNN for Medical Image Segmentation.

U-Net Training with Instance-Layer Normalization ACNN: a Full Resolution DCNN for Medical Image Segmentation

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-14T11:58:44.934385Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.