Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-07-09T00:43:19.567761Z
Paper Citation Record · LEDGER
Hybrid Least Squares/Gradient Descent Methods for MIONets
As of 9 August 2026, this Paper Citation Record lists 71 of 71 outbound references and 0 inbound Pith citation observations for arXiv:2607.06976.
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
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
71 of 71 outbound references displayed
- verified exact2
- verified fuzzy53
- unresolved10
- parse uncertain2
- malformed identifier0
- metadata mismatch4
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation a27e8b60-f617-4e9e-a185-f0d56c68d197 · outbound
This paper cites Learning nonlinear operators via.
Hybrid Least Squares/Gradient Descent Methods for MIONets Learning nonlinear operators via
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T00:45:49.386388Z
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 dad7418f-bc5a-4fc1-b9b8-687e50dbdd16 · outbound
This paper cites IEEE Transactions on Neural Networks , volume=.
Hybrid Least Squares/Gradient Descent Methods for MIONets IEEE Transactions on Neural Networks , volume=
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T00:45:49.388048Z
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 f9916e4e-50ac-4a5f-8797-223f0ef53eb0 · outbound
This paper cites Mathematical and Scientific Machine Learning , pages=.
Hybrid Least Squares/Gradient Descent Methods for MIONets Mathematical and Scientific Machine Learning , pages=
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T00:45:49.425913Z
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 dbe7f4a6-48cd-4ef8-ac22-785d8c35b65f · outbound
This paper cites Learning the solution operator of parametric partial differential equations with physics-informed.
Hybrid Least Squares/Gradient Descent Methods for MIONets Learning the solution operator of parametric partial differential equations with physics-informed
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T00:45:49.397635Z
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 1bdf3887-ae6f-421c-9ddd-1fbd04e0fcd5 · outbound
This paper cites 2022 , publisher=.
Hybrid Least Squares/Gradient Descent Methods for MIONets 2022 , publisher=
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T00:45:49.383326Z
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 024d32bd-f90a-4fcc-8277-0c6a60dea39c · outbound
This paper cites Adam: A Method for Stochastic Optimization.
Hybrid Least Squares/Gradient Descent Methods for MIONets Adam: A Method for Stochastic Optimization
Reference 6
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-09T00:45:49.149542Z
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 a6645fab-147a-4519-af8d-594360d35c2a · outbound
This paper cites Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics , pages=.
Hybrid Least Squares/Gradient Descent Methods for MIONets Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics , pages=
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T00:45:49.411655Z
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 46149e43-66a9-497e-8cb3-efbb52bf6c8f · outbound
This paper cites Proceedings of the IEEE International Conference on Computer Vision , pages=.
Hybrid Least Squares/Gradient Descent Methods for MIONets Proceedings of the IEEE International Conference on Computer Vision , pages=
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T00:45:49.376431Z
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 f1318910-f9e5-4a17-b80c-d5c7385f89c5 · outbound
This paper cites Mathematical Proceedings of the Cambridge Philosophical Society , author=.
Hybrid Least Squares/Gradient Descent Methods for MIONets Mathematical Proceedings of the Cambridge Philosophical Society , author=
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T00:45:49.462332Z
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 c87f5846-0e8d-488c-b80d-63545ae597d2 · outbound
This paper cites Matemati.
Hybrid Least Squares/Gradient Descent Methods for MIONets Matemati
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T00:45:49.419530Z
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 f4557e27-95f3-4a78-92f4-460f7f896267 · outbound
This paper cites Selected Papers Volume I , pages=.
Hybrid Least Squares/Gradient Descent Methods for MIONets Selected Papers Volume I , pages=
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T00:45:49.371694Z
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 3c6b87f4-88c3-4374-8a0c-98094d379e55 · outbound
This paper cites an unresolved cited work.
Hybrid Least Squares/Gradient Descent Methods for MIONets Unresolved cited work
Reference 12
- Resolution
- unresolved
- raw_fallback, observed 2026-07-09T00:45:49.370043Z
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 ceba4a70-f642-4c27-acb3-63e833638b4b · outbound
This paper cites Partitioned neural network approximation for partial differential equations enhanced with.
Hybrid Least Squares/Gradient Descent Methods for MIONets Partitioned neural network approximation for partial differential equations enhanced with
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T00:45:49.380006Z
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 a1e6b239-7bd9-4c84-be2a-fc96c70442e2 · outbound
This paper cites Magnus and H.
Hybrid Least Squares/Gradient Descent Methods for MIONets Magnus and H
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T00:45:49.395885Z
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 a85ff9f2-4b69-409a-bcdd-65314e70605e · outbound
This paper cites , journal=.
Hybrid Least Squares/Gradient Descent Methods for MIONets , journal=
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T00:45:49.465266Z
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 e91ac9ce-ba8a-46df-98e2-adc3825a3df0 · outbound
This paper cites The solution of the matrix equations.
Hybrid Least Squares/Gradient Descent Methods for MIONets The solution of the matrix equations
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T00:45:49.470514Z
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 a794ba80-2f4e-498e-87e6-da6774a3644b · outbound
This paper cites Algorithm 432.
Hybrid Least Squares/Gradient Descent Methods for MIONets Algorithm 432
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T00:45:49.459108Z
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 715597b3-f1da-418c-95b3-404848dd8e4c · outbound
This paper cites Doklady Akademii Nauk , volume=.
Hybrid Least Squares/Gradient Descent Methods for MIONets Doklady Akademii Nauk , volume=
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T00:45:49.457331Z
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 3e0709e7-07d2-4953-b317-14cd6edb6ffa · outbound
This paper cites SIAM Journal on Matrix Analysis and Applications , volume=.
Hybrid Least Squares/Gradient Descent Methods for MIONets SIAM Journal on Matrix Analysis and Applications , volume=
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T00:45:49.460682Z
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 3ed3a2ea-f064-436a-99c1-696a83557c30 · outbound
This paper cites 2009 , school=.
Hybrid Least Squares/Gradient Descent Methods for MIONets 2009 , school=
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T00:45:49.463822Z
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 11611da0-b665-4304-8748-c802aab2d2a2 · outbound
This paper cites an unresolved cited work.
Hybrid Least Squares/Gradient Descent Methods for MIONets Unresolved cited work
Reference 21
- Resolution
- unresolved
- raw_fallback, observed 2026-07-09T00:45:49.468378Z
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 0c1d6957-7a5e-43ab-b27a-32cc6de2edef · outbound
This paper cites Journal of the American Statistical Association , volume=.
Hybrid Least Squares/Gradient Descent Methods for MIONets Journal of the American Statistical Association , volume=
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T00:45:49.447325Z
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 8cb02eb7-a417-41aa-bd30-8cb3baa9988a · outbound
This paper cites Computer Methods in Applied Mechanics and Engineering , volume=.
Hybrid Least Squares/Gradient Descent Methods for MIONets Computer Methods in Applied Mechanics and Engineering , volume=
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T00:45:49.445626Z
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 f14c2af7-beee-48fe-9e26-ca0115c2990f · outbound
This paper cites Mathematics of Control, Signals and Systems , volume=.
Hybrid Least Squares/Gradient Descent Methods for MIONets Mathematics of Control, Signals and Systems , volume=
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T00:45:49.449088Z
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 14527ddf-50e9-4215-9425-6640e84ff5ac · outbound
This paper cites Neural Networks , volume=.
Hybrid Least Squares/Gradient Descent Methods for MIONets Neural Networks , volume=
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T00:45:49.453841Z
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 4cf57fbc-1a0e-49a9-a424-3746f65feea5 · outbound
This paper cites Applied and Computational Harmonic Analysis , volume=.
Hybrid Least Squares/Gradient Descent Methods for MIONets Applied and Computational Harmonic Analysis , volume=
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T00:45:49.437564Z
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 48d4d75b-1585-47c9-957d-24682d2c72cc · outbound
This paper cites Refinement and universal approximation via sparsely connected.
Hybrid Least Squares/Gradient Descent Methods for MIONets Refinement and universal approximation via sparsely connected
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T00:45:49.440870Z
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 8f6df7d4-8a37-4b2c-8a3d-5f87e4539c2c · outbound
This paper cites IEEE Transactions on Information Theory , volume=.
Hybrid Least Squares/Gradient Descent Methods for MIONets IEEE Transactions on Information Theory , volume=
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T00:45:49.439147Z
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 16ae125b-030c-40f7-87d0-6378307c8298 · outbound
This paper cites Neural Networks , volume=.
Hybrid Least Squares/Gradient Descent Methods for MIONets Neural Networks , volume=
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T00:45:49.442424Z
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 c79b461f-bb5e-4258-a0d0-14c60ef0010a · outbound
This paper cites Advances in Neural Information Processing Systems , volume=.
Hybrid Least Squares/Gradient Descent Methods for MIONets Advances in Neural Information Processing Systems , volume=
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T00:45:49.455443Z
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 371d49ab-6b55-470b-9ef1-48fdb66b39a7 · outbound
This paper cites Proceedings of the IEEE conference on computer vision and pattern recognition , pages=.
Hybrid Least Squares/Gradient Descent Methods for MIONets Proceedings of the IEEE conference on computer vision and pattern recognition , pages=
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T00:45:49.432784Z
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 f42a60dd-7567-47af-8647-5823a0990331 · outbound
This paper cites Advances in Neural Information Processing Systems , volume=.
Hybrid Least Squares/Gradient Descent Methods for MIONets Advances in Neural Information Processing Systems , volume=
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T00:45:49.434405Z
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 b1876a6d-1970-4570-940d-e2d1305707fc · outbound
This paper cites International Journal of Neural Systems , volume=.
Hybrid Least Squares/Gradient Descent Methods for MIONets International Journal of Neural Systems , volume=
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T00:45:49.427577Z
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 8d6d6ea5-2b94-4eeb-8028-a30030c76181 · outbound
This paper cites 2011 , publisher=.
Hybrid Least Squares/Gradient Descent Methods for MIONets 2011 , publisher=
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T00:45:49.424272Z
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 fe111056-c3bd-449e-9796-30d31ac3aaae · outbound
This paper cites A Survey on Universal Approximation Theorems.
Hybrid Least Squares/Gradient Descent Methods for MIONets A Survey on Universal Approximation Theorems
Reference 35
- Resolution
- verified exact
- local_arxiv, observed 2026-07-09T00:45:49.156566Z
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 993be4f3-9cfd-4df8-a90b-d908484722bf · outbound
This paper cites 2018 , publisher=.
Hybrid Least Squares/Gradient Descent Methods for MIONets 2018 , publisher=
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T00:45:49.373282Z
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 56bb042b-b079-469a-9074-32ebcd80c0bb · outbound
This paper cites IEEE Signal Processing Letters , volume=.
Hybrid Least Squares/Gradient Descent Methods for MIONets IEEE Signal Processing Letters , volume=
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T00:45:49.421133Z
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 af2689ea-4ce7-4470-8eeb-b62708e5fee8 · outbound
This paper cites Enhanced line search: A novel method to accelerate.
Hybrid Least Squares/Gradient Descent Methods for MIONets Enhanced line search: A novel method to accelerate
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T00:45:49.430920Z
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 413a05da-23fd-41f6-a83b-ad80b2ab5ad0 · outbound
This paper cites 1997 , publisher=.
Hybrid Least Squares/Gradient Descent Methods for MIONets 1997 , publisher=
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T00:45:49.416429Z
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 b18c6ca2-2295-467e-b604-74ea70a96aed · outbound
This paper cites Journal of Computational Physics , volume=.
Hybrid Least Squares/Gradient Descent Methods for MIONets Journal of Computational Physics , volume=
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T00:45:49.414892Z
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 96fce1c9-6e6f-47bf-a8d6-ce001bc6d515 · outbound
This paper cites Journal of Machine Learning Research , volume=.
Hybrid Least Squares/Gradient Descent Methods for MIONets Journal of Machine Learning Research , volume=
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T00:45:49.417990Z
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 7cb1cfc0-caee-4331-ba2c-3b57d7bd97b0 · outbound
This paper cites an unresolved cited work.
Hybrid Least Squares/Gradient Descent Methods for MIONets Unresolved cited work
Reference 42
- Resolution
- unresolved
- raw_fallback, observed 2026-07-09T00:45:49.435933Z
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 f0cfd981-24d9-4dd1-8530-21bf296b1157 · outbound
This paper cites an unresolved cited work.
Hybrid Least Squares/Gradient Descent Methods for MIONets Unresolved cited work
Reference 43
- Resolution
- unresolved
- raw_fallback, observed 2026-07-09T00:45:49.450642Z
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 9c1eac63-0a23-4bba-9048-33b2e9096ce6 · outbound
This paper cites 2016 , organization=.
Hybrid Least Squares/Gradient Descent Methods for MIONets 2016 , organization=
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T00:45:49.399168Z
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 ad92f956-0ff5-4645-bc03-680a6dd630f6 · outbound
This paper cites an unresolved cited work.
Hybrid Least Squares/Gradient Descent Methods for MIONets Unresolved cited work
Reference 45
- Resolution
- unresolved
- raw_fallback, observed 2026-07-09T00:45:49.403646Z
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 029bf184-c462-434e-b49c-6fabf9e22df9 · outbound
This paper cites Advances in Neural Information Processing Systems , volume=.
Hybrid Least Squares/Gradient Descent Methods for MIONets Advances in Neural Information Processing Systems , volume=
Reference 46
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T00:45:49.394333Z
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 161cfeea-e74a-4402-a9e5-4fcda181a6fc · outbound
This paper cites , author=.
Hybrid Least Squares/Gradient Descent Methods for MIONets , author=
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T00:45:49.405290Z
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 9db8595b-d066-4e26-8740-57b934808f3a · outbound
This paper cites Domain Decomposition Methods in Science and Engineering XXVI , pages=.
Hybrid Least Squares/Gradient Descent Methods for MIONets Domain Decomposition Methods in Science and Engineering XXVI , pages=
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T00:45:49.392734Z
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 c2574d0c-41dd-496d-83bc-f03253d2dc3e · outbound
This paper cites Neural Networks , volume=.
Hybrid Least Squares/Gradient Descent Methods for MIONets Neural Networks , volume=
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T00:45:49.391125Z
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 2250c648-01d0-4ee7-9eee-993b1357f294 · outbound
This paper cites Physics of Fluids , volume=.
Hybrid Least Squares/Gradient Descent Methods for MIONets Physics of Fluids , volume=
Reference 50
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T00:45:49.384889Z
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 1df1a467-752b-4681-86d9-aa0d9229ad8b · outbound
This paper cites Searching for Activation Functions.
Hybrid Least Squares/Gradient Descent Methods for MIONets Searching for Activation Functions
Reference 51
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-09T00:45:49.151858Z
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 8ed539fc-a18e-4bcf-98a7-6dc1015d2a4a · outbound
This paper cites On the limited memory.
Hybrid Least Squares/Gradient Descent Methods for MIONets On the limited memory
Reference 52
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T00:45:49.400741Z
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 507558ce-a68a-4d76-b4ae-bd7bd3dfffd4 · outbound
This paper cites an unresolved cited work.
Hybrid Least Squares/Gradient Descent Methods for MIONets Unresolved cited work
Reference 53
- Resolution
- parse uncertain
- raw_fallback, observed 2026-07-09T00:45:49.466888Z
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 735de633-049f-49c4-96c5-4042b80f8874 · outbound
This paper cites Hybrid Least Squares/Gradient Descent Methods for.
Hybrid Least Squares/Gradient Descent Methods for MIONets Hybrid Least Squares/Gradient Descent Methods for
Reference 54
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T00:45:49.381780Z
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 066b2d5b-de98-426f-8c03-0d7643460d11 · outbound
This paper cites A hybrid iterative method based on.
Hybrid Least Squares/Gradient Descent Methods for MIONets A hybrid iterative method based on
Reference 55
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T00:45:49.452280Z
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 261703f8-617a-4825-be27-fda59d6a3967 · outbound
This paper cites Schauder bases in.
Hybrid Least Squares/Gradient Descent Methods for MIONets Schauder bases in
Reference 56
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T00:45:49.472002Z
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 c14b03d0-9e32-4c69-807f-a8dc93909c22 · outbound
This paper cites Zur theorie stetiger abbildungen in funktionalr.
Hybrid Least Squares/Gradient Descent Methods for MIONets Zur theorie stetiger abbildungen in funktionalr
Reference 57
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T00:45:49.444049Z
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 4b16a523-87b3-4798-b0d1-a53df89cde4f · outbound
This paper cites an unresolved cited work.
Hybrid Least Squares/Gradient Descent Methods for MIONets Unresolved cited work
Reference 58
- Resolution
- parse uncertain
- raw_fallback, observed 2026-07-09T00:45:49.422754Z
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 dc5d8f2b-d11d-4194-ab89-f26946c13e31 · outbound
This paper cites an unresolved cited work.
Hybrid Least Squares/Gradient Descent Methods for MIONets Unresolved cited work
Reference 59
- Resolution
- unresolved
- raw_fallback, observed 2026-07-09T00:45:49.368447Z
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 47397e78-9d4a-4b14-bdfc-19416cdc815f · outbound
This paper cites Furuichi, H.
Hybrid Least Squares/Gradient Descent Methods for MIONets Furuichi, H
Reference 60
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-09T00:45:48.809712Z
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 4638aa05-6749-442e-95d2-f1135570a314 · outbound
This paper cites The Annals of Statistics , number =.
Hybrid Least Squares/Gradient Descent Methods for MIONets The Annals of Statistics , number =
Reference 61
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T00:45:49.389573Z
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 cd79534c-cbb4-43cd-872b-049dd4f295b3 · outbound
This paper cites arXiv preprint math.GM/0508053 , year=.
Hybrid Least Squares/Gradient Descent Methods for MIONets arXiv preprint math.GM/0508053 , year=
Reference 62
- Resolution
- verified exact
- arxiv_id, observed 2026-07-09T00:45:49.159556Z
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 e1cd2c6f-8519-4616-90a3-7c77b0aa6050 · outbound
This paper cites an unresolved cited work.
Hybrid Least Squares/Gradient Descent Methods for MIONets Unresolved cited work
Reference 63
- Resolution
- unresolved
- raw_fallback, observed 2026-07-09T00:45:49.402226Z
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 64adba85-1f18-47ea-b0ea-6b040eb0c783 · outbound
This paper cites Advances in Neural Information Processing Systems , volume=.
Hybrid Least Squares/Gradient Descent Methods for MIONets Advances in Neural Information Processing Systems , volume=
Reference 64
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T00:45:49.413234Z
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 00e3c16b-a5ff-474a-9086-ea27fb62fec5 · outbound
This paper cites an unresolved cited work.
Hybrid Least Squares/Gradient Descent Methods for MIONets Unresolved cited work
Reference 65
- Resolution
- unresolved
- raw_fallback, observed 2026-07-09T00:45:49.410040Z
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 79fbfa83-2194-4fe7-a293-ab301136e5f4 · outbound
This paper cites 2024 , publisher=.
Hybrid Least Squares/Gradient Descent Methods for MIONets 2024 , publisher=
Reference 66
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T00:45:49.408540Z
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 888289e4-a495-46a4-b8b1-0857d3af6986 · outbound
This paper cites Physical Review Research , volume=.
Hybrid Least Squares/Gradient Descent Methods for MIONets Physical Review Research , volume=
Reference 67
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T00:45:49.378136Z
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 a1547d3e-1ec8-4051-9ed7-80b479472d6c · outbound
This paper cites an unresolved cited work.
Hybrid Least Squares/Gradient Descent Methods for MIONets Unresolved cited work
Reference 68
- Resolution
- unresolved
- raw_fallback, observed 2026-07-09T00:45:49.407069Z
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 7ad20d13-9274-4edc-b49f-94de8a3cd69f · outbound
This paper cites an unresolved cited work.
Hybrid Least Squares/Gradient Descent Methods for MIONets Unresolved cited work
Reference 69
- Resolution
- unresolved
- raw_fallback, observed 2026-07-09T00:45:49.429103Z
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 11ecd234-06a7-4066-8734-c1c80d980320 · outbound
This paper cites , booktitle =.
Hybrid Least Squares/Gradient Descent Methods for MIONets , booktitle =
Reference 70
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T00:45:49.374814Z
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 9e8b3549-9265-4be7-bee0-d9eed8bc7e3b · outbound
This paper cites Tensor Transpose and Its Properties.
Hybrid Least Squares/Gradient Descent Methods for MIONets Tensor Transpose and Its Properties
Reference 71
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-09T00:45:49.154104Z
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.
Pith citing papers
No inbound Pith citation observations are available.