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

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

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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

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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

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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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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

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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

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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

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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

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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

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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

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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

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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

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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

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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 2026-08-08T06:32:00.761636+00:00.

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

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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 2026-08-08T06:32:00.761636+00:00.

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

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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

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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

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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

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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 2026-08-08T06:32:00.761636+00:00.

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 2026-08-08T06:32:00.761636+00:00.

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 2026-08-08T06:32:00.761636+00:00.

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 2026-08-08T06:32:00.761636+00:00.

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

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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

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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

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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 2026-08-08T06:32:00.761636+00:00.

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 2026-08-08T06:32:00.761636+00:00.

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

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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

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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 2026-08-08T06:32:00.761636+00:00.

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

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Unavailable: canonical work link unavailable.

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 2026-08-08T06:32:00.761636+00:00.

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 2026-08-08T06:32:00.761636+00:00.

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

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Source-reported events for the cited work

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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 2026-08-08T06:32:00.761636+00:00.

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 2026-08-08T06:32:00.761636+00:00.

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 2026-08-08T06:32:00.761636+00:00.

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 2026-08-08T06:32:00.761636+00:00.

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 2026-08-08T06:32:00.761636+00:00.

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 2026-08-08T06:32:00.761636+00:00.

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

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Source-reported events for the cited work

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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 2026-08-08T06:32:00.761636+00:00.

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 2026-08-08T06:32:00.761636+00:00.

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

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Source-reported events for the cited work

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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

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Unavailable: canonical work link unavailable.

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 2026-08-08T06:32:00.761636+00:00.

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 2026-08-08T06:32:00.761636+00:00.

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 2026-08-08T06:32:00.761636+00:00.

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 2026-08-08T06:32:00.761636+00:00.

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 2026-08-08T06:32:00.761636+00:00.

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Reference resolution

Outbound references

Pith citing papers