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Paper Citation Record · LEDGER

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure

As of 10 August 2026, this Paper Citation Record lists 58 of 58 outbound references and 0 inbound Pith citation observations for arXiv:2507.04682.

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

pith.paper-citation-record.v1
2507.04682 v1

Coverage vector

measured 58 of 58 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:47:01.664288Z

measured 58 of 58 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

58 of 58 outbound references displayed

  • verified exact21
  • verified fuzzy9
  • unresolved13
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch15

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8faf5960-c954-4ccd-bd13-9df04304cc3c · outbound

This paper cites , author Sano, S.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure , author Sano, S

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-06T19:46:55.284760Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:46:55.284760Z digest=sha256:8de81c952a0ec1f7fc2954451d9a7d1eaf417e8f2082df456ca7a6748bc62ab2

Observation 1b5a6b78-9634-43a4-a8e7-2c9b909ebbd2 · outbound

This paper cites , author Wang, Z.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure , author Wang, Z

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-06T19:46:55.329086Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:46:55.329086Z digest=sha256:bc6a196cb9c95279fcdd6626e8f0b196399fade903f7dc6f00d2cc74f50cf112

Observation fa9697e4-b74f-4c0a-a283-69b8f552cde7 · outbound

This paper cites , author Spelman, D.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure , author Spelman, D

Reference 3

Resolution
verified exact
doi, observed 2026-08-06T19:47:04.992120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T19:46:55.414852Z digest=sha256:0494b60ed15ea2db29252e37d63cb896be3f1bb9175403ef02b4c1809daa5adb

Observation 6d3ae783-ef32-4ca4-bd17-f5aa2b0e8777 · outbound

This paper cites , author Chen, H.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure , author Chen, H

Reference 4

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unresolved
no resolver link, observed 2026-08-06T19:46:55.497070Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:46:55.497070Z digest=sha256:53852c8082cce1e8698f5060c7e80405d4bb7720bfc29ff825bafee32324d5d0

Observation 2d0f4604-77d6-4ca2-bcb6-f28a5c8d7207 · outbound

This paper cites , author Sansalone, J.J.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure , author Sansalone, J.J

Reference 5

Resolution
metadata mismatch
raw_fallback, observed 2026-08-06T19:47:08.196137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T19:46:55.578968Z digest=sha256:ff049ceef7ded5c3ce8b98231bf698a4bd3a22a0e16879dab21a01a48a0dfd94

Observation 65f85672-f0d1-4a18-ae09-e136fd4dc4b5 · outbound

This paper cites , author Sansalone, J.J.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure , author Sansalone, J.J

Reference 6

Resolution
verified exact
doi, observed 2026-08-06T19:47:04.816055Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T19:46:55.672283Z digest=sha256:c05e2ce016916a1c1f99c03603ef67c58a792361acf413a959a3b5e13ed45538

Observation 8796a51f-9458-421d-b218-1e7b01238336 · outbound

This paper cites , author Sansalone, J.J.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure , author Sansalone, J.J

Reference 7

Resolution
verified exact
doi, observed 2026-08-06T19:47:04.704661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T19:46:55.757607Z digest=sha256:c7760f247963620f5a26496f5402221c3911d62e1fac6d6a8d9dfcf3b262025b

Observation 9da65fd4-2e45-49b7-8383-57150832a9c0 · outbound

This paper cites title Clean oceans and the blue economy – overview 2024.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure title Clean oceans and the blue economy – overview 2024

Reference 8

Resolution
verified exact
doi, observed 2026-08-06T19:47:04.595897Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T19:46:55.849353Z digest=sha256:dbbaf1a181f3b2fa549e2a506cd398899851b061de3b4bff35461f8c3279ab2b

Observation 6037289d-7a37-4a90-ac33-93a63839cf14 · outbound

This paper cites , author Sansalone, J.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure , author Sansalone, J

Reference 9

Resolution
metadata mismatch
raw_fallback, observed 2026-08-06T19:47:08.076006Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T19:46:55.936315Z digest=sha256:7f194781261d39c3f1ae81ad68ceb26da2878b8b157ecf0aafc88c29737bdcd7

Observation b6ed2a8d-cfcc-48ba-ae94-03c9d0b29465 · outbound

This paper cites , author Sansalone, J.J.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure , author Sansalone, J.J

Reference 11

Resolution
verified exact
doi, observed 2026-08-06T19:47:04.436827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T19:46:56.082846Z digest=sha256:b36e285fe0365b9c5e086fa36713583342f5a2008c8e9cf1ea7d7fd09e23b9d0

Observation 8b1d2960-cf97-4348-a228-8cac2361b3f9 · outbound

This paper cites , author Kapelan, Z.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure , author Kapelan, Z

Reference 12

Resolution
verified exact
doi, observed 2026-08-06T19:47:04.310422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T19:46:56.148327Z digest=sha256:c5cde988b9bd1b76d75fe83e3fb374bfc34b57032d679d0192516f168cc06ed9

Observation eda0f426-8325-4e2c-a583-5ad2bf36634e · outbound

This paper cites , year 2010.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure , year 2010

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:47:08.860014Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T19:46:56.220612Z digest=sha256:52c33480a348306dd52df3618facfcd46682e4020438218309c99c0298c21e8c

Observation 58ca946a-a34f-4f69-960e-af9d98dce87f · outbound

This paper cites , author Ma, C.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure , author Ma, C

Reference 14

Resolution
metadata mismatch
raw_fallback, observed 2026-08-06T19:47:07.814960Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T19:46:56.304937Z digest=sha256:db62e7f82be818992f6f6d8539522587d8a262a1b4b4e46929f1279cf3454489

Observation 5772f5d8-d06b-4ee4-8547-5f93035127b5 · outbound

This paper cites , author Cannon, L.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure , author Cannon, L

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:47:08.814044Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T19:46:56.390375Z digest=sha256:920c17f66f81467e24ffa86c02966204521046d35deddfb02e1f12f53ecda7de

Observation a54dded8-40da-414f-9e30-fe4fea7ac8a8 · outbound

This paper cites MIONet: Learning multiple-input operators via tensor product.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure MIONet: Learning multiple-input operators via tensor product

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-06T19:46:56.450470Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:46:56.450470Z digest=sha256:826d688b22b35a702025ccd4006489f70fb208983f16ccfb534410616f0cc4c8

Observation 5730da00-7834-4ddf-a4bc-75982e494887 · outbound

This paper cites Characterizing possible failure modes in physics-informed neural networks.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure Characterizing possible failure modes in physics-informed neural networks

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-06T19:46:56.517375Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:46:56.517375Z digest=sha256:a5fd3c24f2c37409dce4ef76d975acc7c81177d0406256941ab1ef799bd7c433

Observation 1bbdbeca-9b65-4922-9406-c6b16c04e393 · outbound

This paper cites , author Bang, K.W.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure , author Bang, K.W

Reference 18

Resolution
verified exact
doi, observed 2026-08-06T19:47:04.195457Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T19:46:56.594649Z digest=sha256:aba81300133fb87aa4a6aba66da2aa3368ab684bf5b8bfb0c646cfe5508eb2b0

Observation 85c94dfb-3cf5-429e-9c8d-bf8f265cea8f · outbound

This paper cites , author Vanrolleghem, P.A.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure , author Vanrolleghem, P.A

Reference 19

Resolution
verified exact
doi, observed 2026-08-06T19:47:04.084236Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T19:46:56.657096Z digest=sha256:4bffa27e940adbfcd426eb62dc4c497d5f5f12c5fa6f1fceb6266ce432166a26

Observation ae25e14d-bc0b-487f-a7ec-81df0095995c · outbound

This paper cites , year 2024.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure , year 2024

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:47:08.770979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 1da36f31-ce3b-461c-971c-d33e216de7bb · outbound

This paper cites , author Balachandar, S.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure , author Balachandar, S

Reference 21

Resolution
verified exact
doi, observed 2026-08-06T19:47:03.912835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T19:46:56.798867Z digest=sha256:02b0b5e6682867e5bc03543dbfa000640dfcf34f3b529090f89939bdc9345aca

Observation 11ba0105-9fd6-49f6-bd33-a2918789d529 · outbound

This paper cites , author Sansalone, J.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure , author Sansalone, J

Reference 23

Resolution
metadata mismatch
raw_fallback, observed 2026-08-06T19:47:07.923597Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T19:46:56.972952Z digest=sha256:7d9dcb3e4003323ae6ab3454b5996b1d8c4de6809fe156ce6e82cfccda36e383

Observation 06d0e3db-d3fb-41e5-9a7a-b2ff07061802 · outbound

This paper cites , author Sansalone, J.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure , author Sansalone, J

Reference 26

Resolution
metadata mismatch
raw_fallback, observed 2026-08-06T19:47:07.528444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T19:46:57.291545Z digest=sha256:51e2f887fa38671d774dfd48fe9da90f2a7f3659c3dbd2c364fbd40bfbfa8910

Observation 1b26f7eb-db95-4564-a925-6e09cdac668b · outbound

This paper cites , author Sansalone, J.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure , author Sansalone, J

Reference 27

Resolution
metadata mismatch
raw_fallback, observed 2026-08-06T19:47:07.395373Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T19:46:57.369865Z digest=sha256:3d4b2fe6e9be019e5da9725a7d7188c6a22dfa8a99b77f9041679a2ac8dd05e6

Observation b158b885-834c-4f5c-9e57-1142e0ffe364 · outbound

This paper cites , author Sansalone, J.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure , author Sansalone, J

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-06T19:46:57.461476Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:46:57.461476Z digest=sha256:01f30696d3f7d651e75b7bdb5f0d8a2d2151e2cee30f3dcf230350838cb9279c

Observation e008f86e-3a11-45bc-8203-307de164c3f0 · outbound

This paper cites , author Shatarah, M.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure , author Shatarah, M

Reference 29

Resolution
metadata mismatch
raw_fallback, observed 2026-08-06T19:47:07.203014Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T19:46:57.539734Z digest=sha256:8c546755888a4390851b7a7d181d05c8ed27902e5606b8a909298e60b3b05129

Observation 7331ab0c-4393-4bf5-b5ae-59f8c8589373 · outbound

This paper cites , author Spelman, D.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure , author Spelman, D

Reference 30

Resolution
metadata mismatch
raw_fallback, observed 2026-08-06T19:47:07.090177Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T19:46:57.686712Z digest=sha256:d9f77b8f170df77505ba4e93ad3399a129b36c21b100f13316b90322749cd2bc

Observation 6000a2ec-6766-4d40-b448-d3dd8a8c301b · outbound

This paper cites , author Spelman, D.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure , author Spelman, D

Reference 31

Resolution
verified exact
doi, observed 2026-08-06T19:47:03.786489Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T19:46:57.824137Z digest=sha256:3bdb142b6e724ad14907523343b4c7234e0d41ac993d9b63ec601a4f42f0cbd7

Observation 84ad43d5-968e-4bc0-8aca-08d1e6319124 · outbound

This paper cites , author Spelman, D.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure , author Spelman, D

Reference 32

Resolution
verified exact
doi, observed 2026-08-06T19:47:03.651726Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T19:46:57.999591Z digest=sha256:51f5dcbbbe584ec87667000c2d7c3d28a7c5a65d7a07021592f26f487fb28384

Observation c02a83ce-4424-48ca-8682-a4469b0cadb1 · outbound

This paper cites , author Kovachki, N.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure , author Kovachki, N

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:47:08.706155Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T19:46:58.117832Z digest=sha256:02a907cd7007598ec438e349f803ea23191e357b021351ab5f6b510d6a8344e6

Observation bfe73ebd-9a82-4947-8514-173f2030406b · outbound

This paper cites Physics-Informed Neural Operator for Learning Partial Differential Equations.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure Physics-Informed Neural Operator for Learning Partial Differential Equations

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-06T19:46:58.293227Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:46:58.293227Z digest=sha256:f3f47f1d191add5c07742729ca61e82f01c9bd5c2157941dfc92b5b9a12c68b4

Observation 013b293e-605e-4a78-8e84-23de2c23f29a · outbound

This paper cites , author Sansalone, J.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure , author Sansalone, J

Reference 35

Resolution
verified exact
doi, observed 2026-08-06T19:47:03.472869Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T19:46:58.449948Z digest=sha256:406437ccafa715880ec98744ab9fb2cecd4a217b5c35dae424b83acce1bfb319

Observation 0a83ad45-5f57-4c5b-a6a9-ab3aa036ec69 · outbound

This paper cites , author Garc \' i a, M.H.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure , author Garc \' i a, M.H

Reference 36

Resolution
metadata mismatch
raw_fallback, observed 2026-08-06T19:47:06.931998Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T19:46:58.646763Z digest=sha256:0995856d5999e8d008d217a3bfdc4d4056ad99cdf7d58338926627d0e6f01f8b

Observation 2938862c-4f29-4e71-b40a-a1f302f4415d · outbound

This paper cites , author Zhang, J.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure , author Zhang, J

Reference 37

Resolution
metadata mismatch
raw_fallback, observed 2026-08-06T19:47:07.654846Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T19:46:58.821702Z digest=sha256:716819722838084c9e4ca86df910dfe3dd83b19728b2d471337b76402464fa6c

Observation 437a6682-5c5c-4209-8910-672bfa2ebc46 · outbound

This paper cites , author Qin, R.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure , author Qin, R

Reference 38

Resolution
verified exact
doi, observed 2026-08-06T19:47:03.291904Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T19:46:58.939403Z digest=sha256:9704293533042ff90c2e6f18183585487f101489491be797a528d9b4dfa95046

Observation 46cafe54-9d4f-4163-b400-d957bb09470a · outbound

This paper cites DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-06T19:46:59.082800Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:46:59.082800Z digest=sha256:3afa034248c52adc2f266c8593ba8ab62ddd1c6b9f71feadb701e3a474330023

Observation bea8136b-8b71-48cb-b619-590fe21d8315 · outbound

This paper cites , author Lu, L.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure , author Lu, L

Reference 40

Resolution
metadata mismatch
raw_fallback, observed 2026-08-06T19:47:06.798556Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T19:46:59.167473Z digest=sha256:7831d159efd6e52cf7851488db307e1d500d67f0ea7b13c6531a1c13b96d5fbf

Observation 96cb7443-c6c7-4779-bed6-7c609c621f9c · outbound

This paper cites , author Luschi, C.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure , author Luschi, C

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:47:08.642294Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T19:46:59.269577Z digest=sha256:01a401d54e045416f3c358e3b352bf57c1002a90f24e7340cb42d9ebf9e7e57a

Observation 538da437-cc39-42af-8239-e005183eff5c · outbound

This paper cites , author Lee, D.H.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure , author Lee, D.H

Reference 42

Resolution
verified exact
doi, observed 2026-08-06T19:47:03.049744Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T19:46:59.375912Z digest=sha256:7b0fb253536ded00ba3c88a2a109b470b69775ab63057c60dffd3bd196e51302

Observation 2acd1953-dca9-4c8a-80f5-aa8db0d3fb6b · outbound

This paper cites , author Lewis, M.J.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure , author Lewis, M.J

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-06T19:46:59.508351Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:46:59.508351Z digest=sha256:06f4b4b44e68753f7aaa800c497e8520b1b6a70e8170c880b5c3ed22ec0c4ada

Observation d2b41849-bf97-4c58-936f-b55a3ff704c0 · outbound

This paper cites , author Cherukumilli, K.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure , author Cherukumilli, K

Reference 44

Resolution
metadata mismatch
raw_fallback, observed 2026-08-06T19:47:06.442756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T19:46:59.632864Z digest=sha256:2d395c7aa71d555f33c3e427d54b7696472d1bb676f1fe03b39282a57baee3f7

Observation 4408a670-4bb7-4cf9-87cf-32e0fc45cd9b · outbound

This paper cites , author Sansalone, J.J.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure , author Sansalone, J.J

Reference 45

Resolution
verified exact
doi, observed 2026-08-06T19:47:02.872307Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T19:46:59.739788Z digest=sha256:6ee0e3de5b8949e27deb9e3ada5edd42145e20d41c019e5fe743aeb68a087933

Observation 828edc98-f066-4259-95e4-5e5f53ac9885 · outbound

This paper cites , year 2012.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure , year 2012

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-06T19:46:59.839575Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:46:59.839575Z digest=sha256:4d6292d9a974ce813ea7586aa52852eb1580d97dc68223c507d96c27285cb3cf

Observation ba72cd84-fa87-4a36-b109-fd0066cbf755 · outbound

This paper cites , author Richards, P.A.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure , author Richards, P.A

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:47:08.587645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T19:46:59.973692Z digest=sha256:4ca1905a77a225bab1c7f506f8fe62990a27fe1fe4710948b3437ded3c9c31f4

Observation 27d861cc-bf89-4eea-a91b-70662322ee5d · outbound

This paper cites , author Hird, J.P.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure , author Hird, J.P

Reference 48

Resolution
verified exact
raw_fallback, observed 2026-08-06T19:47:06.204294Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T19:47:00.097813Z digest=sha256:14daf351ebcb8fca64918bb69b67d7ebe1dbd2570a29cddad91b9bdf9b4fb5d0

Observation edc3111d-ad31-4ecc-b266-52aa832df4d6 · outbound

This paper cites , author Pathapati, S.S.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure , author Pathapati, S.S

Reference 49

Resolution
verified exact
doi, observed 2026-08-06T19:47:02.665167Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T19:47:00.199887Z digest=sha256:605bfdc620c51b1467e9911dbfb46ebe875a4b1269f8ca9b6dad6b4337a9363a

Observation 5ac728c2-26aa-4a89-b690-7c5ff56dede9 · outbound

This paper cites , author Sansalone, J.J.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure , author Sansalone, J.J

Reference 50

Resolution
verified exact
doi, observed 2026-08-06T19:47:02.447357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T19:47:00.302265Z digest=sha256:75908e0f43f61d40b7732b0c5f79a939d82ddaaa8f87e1661a601cbd1bb7536c

Observation ee3577fc-41ba-4d4e-84cb-11443f383f7c · outbound

This paper cites , author Sansalone, J.J.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure , author Sansalone, J.J

Reference 52

Resolution
metadata mismatch
raw_fallback, observed 2026-08-06T19:47:05.934379Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T19:47:00.472788Z digest=sha256:587624d4d67cf1dfaedab940d86cd4f6e80e729a67a2e0aeeeeffaa6616ab311

Observation aa515729-b470-4556-bff1-c0c6ae5930c0 · outbound

This paper cites , author Scanlon, B.R.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure , author Scanlon, B.R

Reference 53

Resolution
verified exact
doi, observed 2026-08-06T19:47:02.290958Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T19:47:00.562874Z digest=sha256:8016549bd63c5a4b10119249495ddb82f568fce39af9d05674adf90eb8cd9b75

Observation 4d13167a-51c8-4ac2-bab7-87a4a1fd9307 · outbound

This paper cites Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-06T19:47:00.699993Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:47:00.699993Z digest=sha256:4eb9ac8db550cd9d8bf2e126caa3485024e429d906396f946622ec479f1a7081

Observation 065fc2e3-0343-4883-b3ce-5701931e3214 · outbound

This paper cites title Stormwater Inlet Controls; Fact Sheet.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure title Stormwater Inlet Controls; Fact Sheet

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:47:08.516865Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T19:47:00.802703Z digest=sha256:839ee95372266509d986aa33b6c2d569e7096d614f8affb06c942954bd815f0b

Observation 88de4acf-c8f0-48a0-90ae-858c81c3d1b1 · outbound

This paper cites title Water Infrastructure Investments.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure title Water Infrastructure Investments

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:47:08.464738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T19:47:00.939455Z digest=sha256:b9f135826f8073b47e94ee8897858cf4c19edd406e269d849751ab9a7806ccc4

Observation 2c790c8f-e1bf-4397-9a55-b971f797923c · outbound

This paper cites Attention Is All You Need.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure Attention Is All You Need

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-06T19:47:01.036808Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:47:01.036808Z digest=sha256:cfc5fff73b0901f69bc126d2bbc0ea3022075d93bc4c9d84656064d065e21893

Observation 67deb52b-a7f7-4390-8392-12c9c02e90ac · outbound

This paper cites Learning the solution operator of parametric partial differential equations with physics-informed DeepOnets.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure Learning the solution operator of parametric partial differential equations with physics-informed DeepOnets

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-06T19:47:01.114992Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:47:01.114992Z digest=sha256:35a17fdd3bdbe1faf20d0749ad2c58c2a3fa13c80c209e85a9dea5227b5e068f

Observation 89d9a8ab-b32b-4b8a-af71-08578fa01d70 · outbound

This paper cites , author Mohseni, O.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure , author Mohseni, O

Reference 59

Resolution
metadata mismatch
raw_fallback, observed 2026-08-06T19:47:05.558045Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T19:47:01.219446Z digest=sha256:1fa4fac578e717d6721c0ebe2afb7eea97d4df68d5c6ab471ad0aa4da0e65a4d

Observation eb927a56-5ce9-4e03-9e7b-1317c9ebdda9 · outbound

This paper cites , author Zhang, J.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure , author Zhang, J

Reference 60

Resolution
metadata mismatch
raw_fallback, observed 2026-08-06T19:47:05.194437Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T19:47:01.329741Z digest=sha256:073d5101397b7c73fcd9f83c32427f7a2ac1fc1274a2893a5590e7fd6d60e948

Observation 55d3cc6b-5438-42ed-bccc-357e1d5ef70a · outbound

This paper cites , author Sansalone, J.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure , author Sansalone, J

Reference 61

Resolution
verified exact
doi, observed 2026-08-06T19:47:02.017954Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T19:47:01.411166Z digest=sha256:b10344497d00702ce75aa4b1ec6c95532205031332b771f64bc319046bbed633

Observation 96604d92-1890-4707-8c90-9b5b3a25ce3b · outbound

This paper cites , author Tylor, N.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure , author Tylor, N

Reference 62

Resolution
verified exact
doi, observed 2026-08-06T19:47:01.823798Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T19:47:01.538880Z digest=sha256:0726130101e1c9faeb8766404ab39f35b39cf15c91eea93980ecee407d2198d2

Observation d3b4e042-efa4-4a0d-aca1-df47b1065050 · outbound

This paper cites write newline.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure write newline

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:47:08.403498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-06T19:47:01.664288Z digest=sha256:733cc65ebeefe0d73c66885483b88454d58388c4fa81c3d7cf5f226640aa8d4f

Pith citing papers

No inbound Pith citation observations are available.