Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-04T16:17:46.358804Z
Paper Citation Record · LEDGER
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing
As of 9 August 2026, this Paper Citation Record lists 87 of 87 outbound references and 2 inbound Pith citation observations for arXiv:2509.15486.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-08T15:33:58.219906Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-08T15:33:59.407622Z
Reference resolution
87 of 87 outbound references displayed
- verified exact14
- verified fuzzy0
- unresolved62
- parse uncertain0
- malformed identifier11
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation bb998661-2dfe-4958-a683-ad4f83d89a97 · outbound
This paper cites Love, Alán Aspuru-Guzik, and Jeremy L.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Love, Alán Aspuru-Guzik, and Jeremy L
Reference 1
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T16:17:36.145217Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6728da10-e570-44a8-b7f6-4a8958a156ec · outbound
This paper cites Booth, and Jonathan Tennyson.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Booth, and Jonathan Tennyson
Reference 2
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T16:17:36.199601Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3b6f903f-a8e0-45ae-8983-ee3843b7c27e · outbound
This paper cites Olson, Matthias Degroote, Peter D.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Olson, Matthias Degroote, Peter D
Reference 3
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T16:17:36.380350Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1d107353-35ff-4c94-a3df-83a462d17010 · outbound
This paper cites Quantum algorithms for quantum chemistry and quantum materials science.Chemi- cal Reviews, 120(22):12685–12717, 2020.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Quantum algorithms for quantum chemistry and quantum materials science.Chemi- cal Reviews, 120(22):12685–12717, 2020
Reference 4
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T16:17:36.545057Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8a340571-7e0e-4542-9007-24d844218a02 · outbound
This paper cites Benjamin, and Xiao Yuan.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Benjamin, and Xiao Yuan
Reference 5
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T16:17:36.638034Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7d82928f-f806-4555-9fdb-da041cface13 · outbound
This paper cites Kottmann, Tim Menke, Wai-Keong Mok, Sukin Sim, Leong-Chuan Kwek, and Alán Aspuru- Guzik.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Kottmann, Tim Menke, Wai-Keong Mok, Sukin Sim, Leong-Chuan Kwek, and Alán Aspuru- Guzik
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T16:17:36.722747Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7fa1c091-b606-425b-a562-162b71bef161 · outbound
This paper cites Izmaylov.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Izmaylov
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T16:17:36.992932Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 812f20b9-3237-4ea6-9bc2-eea29355ab93 · outbound
This paper cites Efficient and noise resilient measurements for quantum chemistry on near-term quantum computers.npj Quantum Information, 7(1):23, 2021.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Efficient and noise resilient measurements for quantum chemistry on near-term quantum computers.npj Quantum Information, 7(1):23, 2021
Reference 8
- Resolution
- malformed identifier
- doi_truncated, observed 2026-08-04T16:19:20.437920Z
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.
Observation 87e383b3-a8b2-432c-8298-efac30c196f1 · outbound
This paper cites Parrish, Edward G.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Parrish, Edward G
Reference 9
- Resolution
- malformed identifier
- no resolver link, observed 2026-08-04T16:17:37.290399Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation dd02e5c1-db6d-4537-8c7a-769f9995a30d · outbound
This paper cites Izmaylov, Tzu-Ching Yen, Robert A.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Izmaylov, Tzu-Ching Yen, Robert A
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T16:17:37.601219Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8308e103-de6a-4602-9aad-5d2fe87e5bfe · outbound
This paper cites Izmaylov.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Izmaylov
Reference 11
- Resolution
- malformed identifier
- no resolver link, observed 2026-08-04T16:17:37.723441Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 96962bc6-f376-4336-941f-5c70b507c47a · outbound
This paper cites Izmaylov.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Izmaylov
Reference 12
- Resolution
- verified exact
- doi, observed 2026-08-04T16:19:20.069176Z
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.
Observation 78653114-ba4e-4424-bd90-cfc424b1e9b4 · outbound
This paper cites Izmaylov.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Izmaylov
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T16:17:37.981216Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 328f8afe-1d62-4acf-bb00-842a4b685c5d · outbound
This paper cites Izmaylov.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Izmaylov
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T16:17:38.105232Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b28eedaf-b634-493b-9afe-76222d9ccde6 · outbound
This paper cites an unresolved cited work.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Unresolved cited work
Reference 15
- Resolution
- verified exact
- doi, observed 2026-08-04T16:19:19.857122Z
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.
Observation 80a53d98-ab79-4a3d-94c1-259270d47846 · outbound
This paper cites Re- ducing molecular electronic hamiltonian sim- ulation cost for linear combination of uni- taries approaches.Quantum Science and Technology, 8(3):035019, may 2023.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Re- ducing molecular electronic hamiltonian sim- ulation cost for linear combination of uni- taries approaches.Quantum Science and Technology, 8(3):035019, may 2023
Reference 16
- Resolution
- verified exact
- doi, observed 2026-08-04T16:19:19.594887Z
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.
Observation ba62f8de-68ad-4761-b043-0d1cea32f0a8 · outbound
This paper cites Izmaylov.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Izmaylov
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T16:17:38.458162Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 30fa4845-8393-45d1-90c5-e1821613c4fb · outbound
This paper cites On scientific understand- ing with artificial intelligence.Nature Re- views Physics, 4(12):761–769, Dec 2022.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing On scientific understand- ing with artificial intelligence.Nature Re- views Physics, 4(12):761–769, Dec 2022
Reference 18
- Resolution
- malformed identifier
- no resolver link, observed 2026-08-04T16:17:38.608144Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 06a7e6d6-2e90-4e83-b7ee-cc95bb3d7a40 · outbound
This paper cites Entangling indepen- dent particles by path identity.Phys.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Entangling indepen- dent particles by path identity.Phys
Reference 19
- Resolution
- verified exact
- doi, observed 2026-08-04T16:19:18.934749Z
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.
Observation fa1ca5bc-3b88-4e64-839e-0611461372fe · outbound
This paper cites Let the flows tell: Solving graph combinatorial problems with gflownets.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Let the flows tell: Solving graph combinatorial problems with gflownets
Reference 20
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T16:17:38.904022Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 27a284ab-dedc-4059-90dc-a80174ddeaf9 · outbound
This paper cites Rl4co: An extensive reinforcement learning for combinatorial optimization benchmark.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Rl4co: An extensive reinforcement learning for combinatorial optimization benchmark
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T16:17:39.045733Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fc9478ea-7ef5-424e-ba61-9063e5112962 · outbound
This paper cites Learning combina- 14 torial optimization algorithms over graphs.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Learning combina- 14 torial optimization algorithms over graphs
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T16:17:39.107969Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8ace398e-bdc1-4375-87c0-00162abf8b87 · outbound
This paper cites Free-energy machine for combinatorial optimization.Nature Com- putational Science, 5(4):322–332, Apr 2025.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Free-energy machine for combinatorial optimization.Nature Com- putational Science, 5(4):322–332, Apr 2025
Reference 23
- Resolution
- malformed identifier
- no resolver link, observed 2026-08-04T16:17:39.207136Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation caf3c4c8-76c3-403e-a1af-84eb19d2afd8 · outbound
This paper cites Multimodal learning with graphs.Na- ture Machine Intelligence, 5(4):340–350, Apr.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Multimodal learning with graphs.Na- ture Machine Intelligence, 5(4):340–350, Apr
Reference 24
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T16:17:39.386786Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 634b39a3-0000-4abd-acde-ce368917b0f9 · outbound
This paper cites Kottmann, Nora Tischler, and Alán Aspuru-Guzik.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Kottmann, Nora Tischler, and Alán Aspuru-Guzik
Reference 25
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T16:17:39.646444Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 97a9d0a6-5e55-4c4b-acb5-5ab9b9e2367c · outbound
This paper cites Vargas–Hernández, Kjell Jorner, Robert Pollice, and Alán Aspuru–Guzik.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Vargas–Hernández, Kjell Jorner, Robert Pollice, and Alán Aspuru–Guzik
Reference 26
- Resolution
- verified exact
- doi, observed 2026-08-04T16:19:18.194816Z
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.
Observation 5563733c-4666-4e24-957d-1ebdce01ea66 · outbound
This paper cites Vargas-Hernández, John Sous, Mona Berciu, and Roman V.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Vargas-Hernández, John Sous, Mona Berciu, and Roman V
Reference 27
- Resolution
- verified exact
- doi, observed 2026-08-04T16:19:17.661167Z
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.
Observation 80049724-a9e2-491c-a871-809de1b89913 · outbound
This paper cites an unresolved cited work.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Unresolved cited work
Reference 28
- Resolution
- malformed identifier
- no resolver link, observed 2026-08-04T16:17:40.047706Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 20a12edb-e6ce-4733-8999-66d62a916986 · outbound
This paper cites Nicoli, Paolo Stornati, Rouven Koch, Miriam Büttner, Robert Okuła, Gorka Muñoz-Gil, Ro- drigo A.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Nicoli, Paolo Stornati, Rouven Koch, Miriam Büttner, Robert Okuła, Gorka Muñoz-Gil, Ro- drigo A
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T16:17:40.213368Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 306f2223-8e6b-4f97-913a-22f2ab153e55 · outbound
This paper cites an unresolved cited work.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Unresolved cited work
Reference 30
- Resolution
- verified exact
- doi, observed 2026-08-04T16:19:17.084888Z
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.
Observation c3fa7fc9-adf6-43f5-a111-d51f60682aa6 · outbound
This paper cites Digital Discov- ery of 100 diverse Quantum Experiments with PyTheus.Quantum, 7:1204, December.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Digital Discov- ery of 100 diverse Quantum Experiments with PyTheus.Quantum, 7:1204, December
Reference 31
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T16:17:40.469527Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 77721420-317f-4264-900e-311910ec3aa7 · outbound
This paper cites Entan- glement by path identity.Phys.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Entan- glement by path identity.Phys
Reference 32
- Resolution
- verified exact
- doi, observed 2026-08-04T16:19:16.444750Z
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.
Observation 0c42815f-75c9-4778-9bd2-943544534d6e · outbound
This paper cites Combinatorial opti- mization and reasoning with graph neural networks, 2023.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Combinatorial opti- mization and reasoning with graph neural networks, 2023
Reference 33
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T16:17:40.842365Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f6f6085d-37e0-4b45-bd30-1342969acac1 · outbound
This paper cites Machine learning for combinatorial optimization: A method- ological tour d’horizon.European Jour- nal of Operational Research, 290(2): 405–421, 2021.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Machine learning for combinatorial optimization: A method- ological tour d’horizon.European Jour- nal of Operational Research, 290(2): 405–421, 2021
Reference 34
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T16:17:40.978009Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8a6a3bfe-a973-4830-afed-23a39142b00c · outbound
This paper cites DOI: 10.22331/q- 2023-12-12-1204.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing DOI: 10.22331/q- 2023-12-12-1204
Reference 35
- Resolution
- malformed identifier
- no resolver link, observed 2026-08-04T16:17:40.584850Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f2c088b5-4d7e-4f8e-a5f1-8b017d2912a3 · outbound
This paper cites Unsupervised Learning for the Elementary Shortest Path Problem.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Unsupervised Learning for the Elementary Shortest Path Problem
Reference 36
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T16:17:41.215727Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 353f3eaa-aa83-407a-b2b7-1ddcc9d1f710 · outbound
This paper cites Artificial- intelligence-driven shot reduction in quan- tum measurement.Chemical Physics Re- views, 5(4):041403, 10 2024.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Artificial- intelligence-driven shot reduction in quan- tum measurement.Chemical Physics Re- views, 5(4):041403, 10 2024
Reference 37
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T16:17:41.383795Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5fe44d8f-4c6f-4af4-ae4a-b3219793fb6c · outbound
This paper cites an unresolved cited work.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Unresolved cited work
Reference 38
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T16:17:41.672180Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9d6164dc-c465-479f-999a-f1f45c3b180e · outbound
This paper cites A review: Machine learn- ing for combinatorial optimization problems in energy areas.Algorithms, 15(6), 2022.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing A review: Machine learn- ing for combinatorial optimization problems in energy areas.Algorithms, 15(6), 2022
Reference 39
- Resolution
- verified exact
- doi, observed 2026-08-04T16:19:15.602068Z
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.
Observation 7db91813-2ad5-4e38-b9c0-ad376a46b374 · outbound
This paper cites an unresolved cited work.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Unresolved cited work
Reference 40
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T16:17:42.028842Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0cb80a51-34f5-492d-9244-1e76969d83d3 · outbound
This paper cites Flow network based generative models for non-iterative diverse candidate generation.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Flow network based generative models for non-iterative diverse candidate generation
Reference 41
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T16:17:42.170397Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 412bae30-255e-4f1a-8c16-47328dbc902d · outbound
This paper cites Willcocks.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Willcocks
Reference 42
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T16:17:42.338973Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d49af0cb-ab4c-4242-8cf4-a7fe97b440eb · outbound
This paper cites GFlowNet Foundations.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing GFlowNet Foundations
Reference 43
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T16:17:42.473950Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0002af71-1e0d-4ee0-a835-a123a2d71e3c · outbound
This paper cites A framework for adaptive MCMC targeting multimodal distributions.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing A framework for adaptive MCMC targeting multimodal distributions
Reference 44
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T16:17:42.537517Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a38aa68f-c29f-4bbd-9ccf-db95abd0a1d7 · outbound
This paper cites Generativeflow- based warm start of the variational quan- tum eigensolver, 2025.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Generativeflow- based warm start of the variational quan- tum eigensolver, 2025
Reference 45
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T16:17:41.912178Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 079731ca-4378-4b3e-bd91-5425992a8854 · outbound
This paper cites GFlowNets for AI-driven scientific discovery.Dig- ital Discovery, 2:557–577, 2023.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing GFlowNets for AI-driven scientific discovery.Dig- ital Discovery, 2:557–577, 2023
Reference 46
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T16:17:42.800964Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7d2aa78a-8fac-4d79-a42b-688449f33cd8 · outbound
This paper cites Discovery of novel reticular materials for carbon dioxide capture using GFlowNets.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Discovery of novel reticular materials for carbon dioxide capture using GFlowNets
Reference 47
- Resolution
- verified exact
- doi, observed 2026-08-04T16:19:14.544750Z
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.
Observation b1e7874f-feeb-4992-8228-f346f5ae681c · outbound
This paper cites Path-filtering in path-integral simulations of open quantum systems using GFlowNets.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Path-filtering in path-integral simulations of open quantum systems using GFlowNets
Reference 48
- Resolution
- verified exact
- doi, observed 2026-08-04T16:19:14.277093Z
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.
Observation 5f23e197-fdc2-4e2d-90fc-8e15f0331549 · outbound
This paper cites an unresolved cited work.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Unresolved cited work
Reference 49
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- unresolved
- no resolver link, observed 2026-08-04T16:17:43.123180Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a6ac42cd-9a19-4e42-8aea-4f6e0959630d · outbound
This paper cites Bravyi and Alexei Yu.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Bravyi and Alexei Yu
Reference 50
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T16:17:43.288985Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d9bc2615-55e7-443c-86df-b28938732740 · outbound
This paper cites URLhttps: //arxiv.org/abs/2312.11840.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing URLhttps: //arxiv.org/abs/2312.11840
Reference 51
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T16:17:43.405529Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation db482644-f787-4a0c-bee7-5329e421c403 · outbound
This paper cites Geometric-informed GFlowNets for Structure-Based Drug Design.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Geometric-informed GFlowNets for Structure-Based Drug Design
Reference 52
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T16:17:42.728123Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b234335f-900e-4d19-b9ca-d9e82d69990e · outbound
This paper cites Encyclopedia of Mathematics and its Applications.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Encyclopedia of Mathematics and its Applications
Reference 53
- Resolution
- verified exact
- doi, observed 2026-08-04T16:19:14.066283Z
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.
Observation bd2525bb-ef44-4a76-8498-006b6376fe31 · outbound
This paper cites Efficient quan- tum measurement of Pauli operators in the presence of finite sampling error.Quantum, 5:385, January 2021.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Efficient quan- tum measurement of Pauli operators in the presence of finite sampling error.Quantum, 5:385, January 2021
Reference 54
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Observation 6057f41d-c7e6-4fe7-a2e9-bd49beff5ff0 · outbound
This paper cites Izmaylov.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Izmaylov
Reference 55
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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.
Observation 10d6e7b5-c722-4128-b139-e9592c9d73f4 · outbound
This paper cites GFlowNets for Hamiltonian decomposition in groups of compatible operators.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing GFlowNets for Hamiltonian decomposition in groups of compatible operators
Reference 56
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Unavailable: canonical work link unavailable.
Observation 611909c0-56a6-4416-9817-5cbdeaddf78f · outbound
This paper cites Tra- jectory balance: Improved credit assignment in gflownets.Advances in Neural Informa- tion Processing Systems, 35:5955–5967, 2022.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Tra- jectory balance: Improved credit assignment in gflownets.Advances in Neural Informa- tion Processing Systems, 35:5955–5967, 2022
Reference 57
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Observation a10987e0-cc63-48ea-a1ed-85f4824434ea · outbound
This paper cites Hagberg, Daniel A.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Hagberg, Daniel A
Reference 58
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Observation b23ea5a0-f6d8-4b66-9b3d-895b921debc2 · outbound
This paper cites Galic: hybrid multi-qubitwise pauli grouping for quantum computing measure- ment.Quantum Science and Technology, 10 (1):015054, dec 2024.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Galic: hybrid multi-qubitwise pauli grouping for quantum computing measure- ment.Quantum Science and Technology, 10 (1):015054, dec 2024
Reference 59
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3aae8b3c-105f-48ae-aec1-2b38b43d91e5 · outbound
This paper cites How powerful are graph neural networks? InInternational Con- ference on Learning Representations, 2019.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing How powerful are graph neural networks? InInternational Con- ference on Learning Representations, 2019
Reference 60
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Unavailable: canonical work link unavailable.
Observation 98d28773-3bb8-4ced-a46a-6ed82da369c3 · outbound
This paper cites Strategies for pre- training graph neural networks.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Strategies for pre- training graph neural networks
Reference 61
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Observation 1a763d26-1d5a-4c84-b7b9-5fbda8611ebd · outbound
This paper cites Tequila: a platform for rapid development of quan- tum algorithms.Quantum Science and Technology, 6(2):024009, mar 2021.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Tequila: a platform for rapid development of quan- tum algorithms.Quantum Science and Technology, 6(2):024009, mar 2021
Reference 62
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3ad85518-7881-4f4c-af34-aa09abc5c74c · outbound
This paper cites Berkelbach, Nick S.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Berkelbach, Nick S
Reference 63
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Observation 55b50644-5769-4b64-a0a0-2dad3854d02a · outbound
This paper cites Blunt, Nikolay A.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Blunt, Nikolay A
Reference 64
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Observation cbf5a307-c4e2-4a91-be2f-972c8342fbe4 · outbound
This paper cites an unresolved cited work.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Unresolved cited work
Reference 65
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Unavailable: canonical work link unavailable.
Observation af39f9cd-2487-4b27-9d45-7fda4c950940 · outbound
This paper cites Johnson, and Artur F.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Johnson, and Artur F
Reference 66
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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.
Observation fafc6f0d-733d-413b-8dc6-03932cb2f68d · outbound
This paper cites Hamilton, Rex Ying, and Jure Leskovec.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Hamilton, Rex Ying, and Jure Leskovec
Reference 67
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Observation 2d1da2f7-ed9b-45e1-9e7c-7144da11dc71 · outbound
This paper cites node2vec: Scalable feature learning for networks.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing node2vec: Scalable feature learning for networks
Reference 68
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Observation 4d44cfef-bdb0-43e0-835e-52e8be45bde3 · outbound
This paper cites Scott.Multivariate Density Estima- tion: Theory, Practice, and Visualization.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Scott.Multivariate Density Estima- tion: Theory, Practice, and Visualization
Reference 69
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Observation b01475d4-b371-40b9-b8e2-3c069013138f · outbound
This paper cites Haste makes waste: A simple approach for scaling graph neural networks.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Haste makes waste: A simple approach for scaling graph neural networks
Reference 70
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Unavailable: canonical work link unavailable.
Observation 9d42fc3a-8f20-4337-a765-9b35633f947b · outbound
This paper cites GraphFM: Improving large-scale GNN train- ing via feature momentum.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing GraphFM: Improving large-scale GNN train- ing via feature momentum
Reference 71
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Observation 95cce21e-2c59-4d0f-83da-1ac8d3cc22b5 · outbound
This paper cites A compre- hensive study on large-scale graph training: Benchmarking and rethinking.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing A compre- hensive study on large-scale graph training: Benchmarking and rethinking
Reference 72
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Observation e41a3c01-9610-4ed4-b67c-c4d51d4eca5c · outbound
This paper cites Adam: A Method for Stochastic Optimization.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Adam: A Method for Stochastic Optimization
Reference 73
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Observation 712c6e20-8f95-4bb7-8bd2-fc93fe68efa8 · outbound
This paper cites Order- preserving GFlownets.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Order- preserving GFlownets
Reference 74
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Observation 8f153351-f69b-4040-8871-a046bb4119d0 · outbound
This paper cites Pre-training and fine- tuning generative flow networks.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Pre-training and fine- tuning generative flow networks
Reference 75
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Observation 3daa62e4-c03d-49e5-ada8-ed51517b28ef · outbound
This paper cites Pretraining generative flow net- works with inexpensive rewards for molec- ular graph generation.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Pretraining generative flow net- works with inexpensive rewards for molec- ular graph generation
Reference 76
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- no resolver link, observed 2026-08-04T16:17:46.053937Z
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Observation 5497dc70-d7f1-4cb0-9ddc-87e074bcc459 · outbound
This paper cites GFlowNet Fine-tuning for Diverse Correct Solutions in Mathematical Reasoning Tasks.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing GFlowNet Fine-tuning for Diverse Correct Solutions in Mathematical Reasoning Tasks
Reference 77
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Observation 85b75c15-e4d6-453f-b382-5acf59d547b7 · outbound
This paper cites Gen- erative augmented flow networks.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Gen- erative augmented flow networks
Reference 78
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Observation 8868c93d-a951-48a9-815b-2b32d8059b71 · outbound
This paper cites Efficient diversity-preserving diffusion alignment via gradient-informed GFlowNets.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Efficient diversity-preserving diffusion alignment via gradient-informed GFlowNets
Reference 79
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Source-reported events for the cited work
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Observation 18a42052-ed0a-4ade-b2f7-789305e8bb7f · outbound
This paper cites Attention is all you need.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Attention is all you need
Reference 81
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Observation 67e5d272-3dc5-4b01-b645-7ed99205876b · outbound
This paper cites an unresolved cited work.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Unresolved cited work
Reference 1371
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- malformed identifier
- no resolver link, observed 2026-08-04T16:17:37.482770Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f5d582fa-d047-477f-9347-f14e18d0ee55 · outbound
This paper cites ISBN 9781450342322.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing ISBN 9781450342322
Reference 2016
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- unresolved
- no resolver link, observed 2026-08-04T16:17:45.427151Z
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Observation 53661f0a-1faa-49b1-ac06-3d71917dd9ab · outbound
This paper cites URL https://doi.org/10.1214/19-AOS1916.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing URL https://doi.org/10.1214/19-AOS1916
Reference 2020
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- no resolver link, observed 2026-08-04T16:17:42.633285Z
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Observation 90e0c272-95db-4d24-8d85-974668a3a979 · outbound
This paper cites URLhttps://link.aps.org/doi/10.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing URLhttps://link.aps.org/doi/10
Reference 2022
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- unresolved
- no resolver link, observed 2026-08-04T16:17:36.850263Z
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Unavailable: canonical work link unavailable.
Observation 6ba0ee33-3e37-458f-9456-0ea1605d9415 · outbound
This paper cites DOI: 10.1038/s42256- 023-00624-6.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing DOI: 10.1038/s42256- 023-00624-6
Reference 2023
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- no resolver link, observed 2026-08-04T16:17:39.569687Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 66299b87-338b-4b24-8ca7-05254876c5d9 · outbound
This paper cites an unresolved cited work.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing Unresolved cited work
Reference 2024
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- unresolved
- no resolver link, observed 2026-08-04T16:17:41.770619Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation efb0dc57-25f1-434b-a6f7-35c266415849 · outbound
This paper cites URLhttps: //doi.org/10.1063/5.0219663.
Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing URLhttps: //doi.org/10.1063/5.0219663
Reference 4070
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Unavailable: canonical work link unavailable.
Pith citing papers
Observation d25c2825-5817-4693-9a41-fb7c312e7625 · inbound
Reducing quantum measurements in qubit-based overlapping grouping methods for quantum energy estimation through better initializations cites this paper.
Reducing quantum measurements in qubit-based overlapping grouping methods for quantum energy estimation through better initializations Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing
Reference 30
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- unresolved
- no resolver link, observed 2026-07-12T07:00:44.574658Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 54f85a8c-07ab-4de3-9b7e-32ee58188a03 · inbound
Machine learning for sample-based quantum diagonalization: generative configuration recovery and the classical-simulability frontier cites this paper.
Machine learning for sample-based quantum diagonalization: generative configuration recovery and the classical-simulability frontier Discrete Flow-Based Generative Models for Measurement Optimization in Quantum Computing
Reference 67
- Resolution
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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.