Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-12T14:26:41.706482Z
Paper Citation Record · LEDGER
Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning
As of 13 August 2026, this Paper Citation Record lists 51 of 51 outbound references and 0 inbound Pith citation observations for arXiv:2411.15360.
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 2026-08-13T06:32:02.005865+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
51 of 51 outbound references displayed
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External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 204f554f-cc06-4fa2-b59b-4b1257688518 · outbound
This paper cites Counting near-infrared single-photons with 95% efficiency,.
Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Counting near-infrared single-photons with 95% efficiency,
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:26:42.566471Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation c465b927-775a-4026-b5cb-0971a50ecdac · outbound
This paper cites Superconducting transition-edge sensors optimized for high- efficiency photon-number resolving detectors,.
Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Superconducting transition-edge sensors optimized for high- efficiency photon-number resolving detectors,
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:26:42.550912Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation e1afe05e-fbe2-4486-a26b-b517d5072527 · outbound
This paper cites FirstAstronomicalApplicationofaCryogenicTransitionEdgeSensor Spectrophotometer,.
Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning FirstAstronomicalApplicationofaCryogenicTransitionEdgeSensor Spectrophotometer,
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:26:42.535270Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation c58e9b2e-46d7-4f76-82f9-2f202fd03100 · outbound
This paper cites SCUBA-2: the 10 000 pixel bolometer camera on the James Clerk Maxwell Telescope,.
Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning SCUBA-2: the 10 000 pixel bolometer camera on the James Clerk Maxwell Telescope,
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:26:42.518830Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation e161c4a6-fc8f-46f4-a93c-766bd04eb2cc · outbound
This paper cites A Review of X-ray Microcalorimeters Based on Superconducting Transition Edge Sensors for Astrophysics and Particle Physics,.
Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning A Review of X-ray Microcalorimeters Based on Superconducting Transition Edge Sensors for Astrophysics and Particle Physics,
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:26:42.502436Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation b3531a7c-b68b-441a-812b-cd4a9156bf78 · outbound
This paper cites Transition-Edge Sensors,.
Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Transition-Edge Sensors,
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:26:42.484577Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 9fbdd346-3836-407e-836a-e181cddb6894 · outbound
This paper cites Review of superconducting transition-edge sensors for x-ray and gamma-ray spectroscopy,.
Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Review of superconducting transition-edge sensors for x-ray and gamma-ray spectroscopy,
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:26:42.467878Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation c0972e07-6e06-4ca5-bfaa-57fa974b086f · outbound
This paper cites Entanglement-enhanced measurement of a completely unknown optical phase,.
Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Entanglement-enhanced measurement of a completely unknown optical phase,
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:26:42.452383Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation bfa2d896-372f-4f08-b0c4-ffe3777db11f · outbound
This paper cites Quantum metrology with imperfect states and detectors,.
Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Quantum metrology with imperfect states and detectors,
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:26:42.436269Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 00cdc5ba-8471-4f0e-ae75-6f0038166c4c · outbound
This paper cites Quantum-enhanced interferometry with large heralded photon-number states,.
Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Quantum-enhanced interferometry with large heralded photon-number states,
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:26:42.419257Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 1d7e1cc2-de3c-4a3f-accc-d1ec897a16f9 · outbound
This paper cites Scalable multiphoton quantum metrology with neither pre- nor post-selected measurements,.
Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Scalable multiphoton quantum metrology with neither pre- nor post-selected measurements,
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:26:42.400628Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 2546a949-26b0-44a8-9dbc-4e5244e6db65 · outbound
This paper cites Few-photonspectralconfocalmicroscopyforcellimagingusingsuperconducting transition edge sensor,.
Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Few-photonspectralconfocalmicroscopyforcellimagingusingsuperconducting transition edge sensor,
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:26:42.384034Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 8f2388d1-b5f7-4e20-a875-f3a3360d3f14 · outbound
This paper cites The computational complexity of linear optics,.
Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning The computational complexity of linear optics,
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:26:42.368816Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 60b0826f-6d59-47d5-8fd4-d667853e3466 · outbound
This paper cites Gaussian Boson Sampling,.
Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Gaussian Boson Sampling,
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:26:42.352673Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 3e673cdd-65f3-4ee3-85b2-bde166a55127 · outbound
This paper cites Detailed study of Gaussian boson sampling,.
Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Detailed study of Gaussian boson sampling,
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:26:42.336725Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation e68a0b4c-31ec-4463-b6ee-61cae2dd84bb · outbound
This paper cites Quantum computational advantage with a programmable photonic processor,.
Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Quantum computational advantage with a programmable photonic processor,
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T14:26:41.314253Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 55867c0a-c6c1-4c3b-abb1-642b752a63de · outbound
This paper cites Conclusive quantum steering with superconducting transition-edge sensors,.
Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Conclusive quantum steering with superconducting transition-edge sensors,
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:26:42.310372Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 1b6c1200-432f-4342-ac64-0b83f8ca36b4 · outbound
This paper cites Significant-loophole-free test of bell’s theorem with entangled photons,.
Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Significant-loophole-free test of bell’s theorem with entangled photons,
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:26:42.294116Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation bc6ab8c7-8e14-469c-a288-c1ac9b661ebe · outbound
This paper cites Proposal for the distribution of multiphoton entanglement with optimal rate-distance scaling,.
Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Proposal for the distribution of multiphoton entanglement with optimal rate-distance scaling,
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:26:42.277972Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation ed2e1f14-b0cc-42bf-b4cb-614c67e39d05 · outbound
This paper cites Generation of optical coherent-state superpositions by number-resolved photon subtraction from the squeezed vacuum,.
Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Generation of optical coherent-state superpositions by number-resolved photon subtraction from the squeezed vacuum,
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:26:42.261715Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation f60b3496-14dd-451b-80c3-cb0e09c6a742 · outbound
This paper cites Non-Gaussian operation based on photon subtraction using a photon-number-resolving detector at a telecommunications wavelength,.
Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Non-Gaussian operation based on photon subtraction using a photon-number-resolving detector at a telecommunications wavelength,
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:26:42.245281Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 0d8c0370-1f75-47ca-a54c-8c481b6485a3 · outbound
This paper cites Engineering Schrödinger cat states with a photonic even-parity detector,.
Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Engineering Schrödinger cat states with a photonic even-parity detector,
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:26:42.229327Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 6407e881-446d-46d6-81dd-6f8bb54a6abd · outbound
This paper cites Multiphoton quantum-state engineering using conditional measurements,.
Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Multiphoton quantum-state engineering using conditional measurements,
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:26:42.213217Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 2145df4b-abdb-41fb-9508-22a2ae88b286 · outbound
This paper cites Progress towards practical qubit computation using approximate Gottesman-Kitaev-Preskill codes,.
Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Progress towards practical qubit computation using approximate Gottesman-Kitaev-Preskill codes,
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:26:42.197902Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 30d5fcc8-4506-4f50-849c-9d10517de45c · outbound
This paper cites Non-Gaussian quantum state generation by multi-photon subtraction at the telecommunication wavelength,.
Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Non-Gaussian quantum state generation by multi-photon subtraction at the telecommunication wavelength,
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:26:42.181582Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 94e7a735-3400-416b-b253-78aacdcf7d93 · outbound
This paper cites Algorithm for finding clusters with a known distribution and its application to photon-number resolution using a superconducting transition-edge sensor,.
Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Algorithm for finding clusters with a known distribution and its application to photon-number resolution using a superconducting transition-edge sensor,
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:26:42.165762Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation f3272d71-a38f-4f97-8b44-9ee990ebac58 · outbound
This paper cites Precisely determining photon-number in real time,.
Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Precisely determining photon-number in real time,
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:26:42.150147Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation efd0db87-da29-46ca-b5b5-0d1d038620cc · outbound
This paper cites Fast transition-edge sensors suitable for photonic quantum computing,.
Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Fast transition-edge sensors suitable for photonic quantum computing,
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:26:42.132062Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 3934cbca-1f62-4751-af4f-c63daf49aff3 · outbound
This paper cites Developmentofsuperconductingsingle-particledetectorTransition-EdgeSensor,.
Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Developmentofsuperconductingsingle-particledetectorTransition-EdgeSensor,
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:26:42.115384Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation f1b60bcc-5ca5-41d0-a9b9-a7be53614090 · outbound
This paper cites Principal component analysis,.
Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Principal component analysis,
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:26:42.098954Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation e82324af-e524-4f3c-af61-b010cf179cdc · outbound
This paper cites Tomography of photon-number resolving continuous-output detectors,.
Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Tomography of photon-number resolving continuous-output detectors,
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:26:42.082108Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 2b213c10-4c39-4d61-81ad-79d62abb73f2 · outbound
This paper cites Nearest neighbor pattern classification,.
Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Nearest neighbor pattern classification,
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:26:42.065762Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 41ffc95f-c3fb-44b3-8f92-ceefb6b9c310 · outbound
This paper cites Scikit-learn: Machine learning in Python,.
Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Scikit-learn: Machine learning in Python,
Reference 33
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T14:26:41.615266Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation af418877-d8c2-4a00-b103-c1b896116f2f · outbound
This paper cites Random Forests,.
Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Random Forests,
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:26:42.037423Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 81c472f0-3ab3-487f-be07-302bf27c2a04 · outbound
This paper cites Liblinear: A library for large linear classification,.
Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Liblinear: A library for large linear classification,
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:26:42.021086Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 6691da8f-a4f8-460b-947f-d663e43a7661 · outbound
This paper cites Libsvm: A library for support vector machines,.
Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Libsvm: A library for support vector machines,
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:26:42.001864Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 537b3f2d-6e55-4da0-8427-a7a1a169c3d5 · outbound
This paper cites Xgboost: A scalable tree boosting system,.
Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Xgboost: A scalable tree boosting system,
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:26:41.984283Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 96f1f80a-a37d-4819-866c-462c681f6602 · outbound
This paper cites TensorFlow: Large-scale machine learning on heterogeneous systems,.
Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning TensorFlow: Large-scale machine learning on heterogeneous systems,
Reference 38
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T14:26:41.641668Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation efde1eb4-127a-43c7-b5d1-27dcd7c4d22a · outbound
This paper cites Network In Network.
Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Network In Network
Reference 39
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T14:26:41.646522Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 57263ded-46c4-47c9-866e-b4bcdeedb381 · outbound
This paper cites Timeseriesclassificationfromscratchwithdeepneuralnetworks: Astrongbaseline,.
Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Timeseriesclassificationfromscratchwithdeepneuralnetworks: Astrongbaseline,
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:26:41.958096Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation b9958a9f-c8c0-4150-a6b6-f06023b2765a · outbound
This paper cites Deep learning for time series classification: a review,.
Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Deep learning for time series classification: a review,
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:26:41.942619Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 2c040619-0474-4792-be11-14080eee05a8 · outbound
This paper cites Density-based clustering based on hierarchical density estimates,.
Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Density-based clustering based on hierarchical density estimates,
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:26:41.926687Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 96178c77-824d-424d-89e6-e6c4dc377062 · outbound
This paper cites hdbscan: Hierarchical density based clustering,.
Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning hdbscan: Hierarchical density based clustering,
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:26:41.911217Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation ee61b9fb-42b2-4b71-8f04-8e6893bf5ea3 · outbound
This paper cites CVXPY: A Python-embedded modeling language for convex optimization,.
Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning CVXPY: A Python-embedded modeling language for convex optimization,
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:26:41.895004Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation a79baeb2-d93b-477a-9dac-19a8733bf856 · outbound
This paper cites A rewriting system for convex optimization problems,.
Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning A rewriting system for convex optimization problems,
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:26:41.877160Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 674ffd68-42e0-439a-9a80-1ecef5f62b0b · outbound
This paper cites Mapping coherence in measurement via full quantum tomography of a hybrid optical detector,.
Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Mapping coherence in measurement via full quantum tomography of a hybrid optical detector,
Reference 46
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:26:41.857003Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 14e59753-76c7-4b48-9282-bf756028ffc0 · outbound
This paper cites The simons observatory: large-scale characterization of 90/150 GHz TES detector modules,.
Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning The simons observatory: large-scale characterization of 90/150 GHz TES detector modules,
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:26:41.840442Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 54076b6f-00a0-4808-a973-bbd0a1088ddf · outbound
This paper cites High_speed_TES_ML,.
Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning High_speed_TES_ML,
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:26:41.824241Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 98291ffd-5301-4d38-9550-e53e7063f02d · outbound
This paper cites Accurate Unsupervised Photon Counting from Transition Edge Sensor Signals.
Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Accurate Unsupervised Photon Counting from Transition Edge Sensor Signals
Reference 49
- Resolution
- verified exact
- local_arxiv, observed 2026-08-12T14:26:41.754453Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 8af6e0f8-5955-4f04-8195-64d9ca426a65 · outbound
This paper cites An application of electrothermal feedback for high resolution cryogenic particle detection,.
Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning An application of electrothermal feedback for high resolution cryogenic particle detection,
Reference 50
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:26:41.808447Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation d47537f7-bef1-4c87-ba96-5e8455c18c97 · outbound
This paper cites SciPy 1.0: Fundamental Algorithms for Scientific Computing in Python,.
Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning SciPy 1.0: Fundamental Algorithms for Scientific Computing in Python,
Reference 51
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:26:41.791179Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Pith citing papers
No inbound Pith citation observations are available.