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Paper Citation Record · LEDGER

GraphNeT 2.0 -- A Deep Learning Library for Neutrino Telescopes

As of 22 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 0 inbound Pith citation observations for arXiv:2501.03817.

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

pith.paper-citation-record.v1
2501.03817 v1

Coverage vector

measured 37 of 37 reference resolution

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Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Source: cited_works

Reference resolution

37 of 37 outbound references displayed

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External citation measurements

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Outbound references

Observation 494de6cc-b623-4b64-8a69-66463dde8383 · outbound

This paper cites The design and performance of IceCube Deep- Core.

GraphNeT 2.0 -- A Deep Learning Library for Neutrino Telescopes The design and performance of IceCube Deep- Core

Reference 1

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Observation 1e6aa01a-13f8-4297-97ea-280d1fe84480 · outbound

This paper cites Astronomy potential of KM3NeT/ARCA.

GraphNeT 2.0 -- A Deep Learning Library for Neutrino Telescopes Astronomy potential of KM3NeT/ARCA

Reference 2

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Observation f398c7f3-0f6a-42a4-b010-c8ed2c9279eb · outbound

This paper cites Low energy event reconstruction in IceCube DeepCore.

GraphNeT 2.0 -- A Deep Learning Library for Neutrino Telescopes Low energy event reconstruction in IceCube DeepCore

Reference 3

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Observation 87fe2370-eecb-4e92-98fc-22aa7fa1ada9 · outbound

This paper cites Improvement in Fast Particle Track Reconstruction with Robust Statis- tics.

GraphNeT 2.0 -- A Deep Learning Library for Neutrino Telescopes Improvement in Fast Particle Track Reconstruction with Robust Statis- tics

Reference 4

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Observation 4e966ec3-52e1-4960-b3f1-af4630c898b3 · outbound

This paper cites A Convolutional Neural Network based Cascade Reconstruction for the IceCube Neutrino Observatory.

GraphNeT 2.0 -- A Deep Learning Library for Neutrino Telescopes A Convolutional Neural Network based Cascade Reconstruction for the IceCube Neutrino Observatory

Reference 5

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Observation 4ca17fe1-df17-4101-8c4a-0a0407f5746b · outbound

This paper cites Combining Maximum-Likelihood with Deep Learning for Event Reconstruction in IceCube.

GraphNeT 2.0 -- A Deep Learning Library for Neutrino Telescopes Combining Maximum-Likelihood with Deep Learning for Event Reconstruction in IceCube

Reference 6

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Observation 30dbd694-661b-4ca5-bd25-a5c34a1228b2 · outbound

This paper cites Reconstruction of Track-like Event in TRIDENT Based on a Submanifold Sparse Convolutional Network.

GraphNeT 2.0 -- A Deep Learning Library for Neutrino Telescopes Reconstruction of Track-like Event in TRIDENT Based on a Submanifold Sparse Convolutional Network

Reference 7

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Observation 3d30ca23-4aa6-4330-a6d0-07c371071460 · outbound

This paper cites Event reconstruction for KM3NeT/ORCA using convolutional neural networks.

GraphNeT 2.0 -- A Deep Learning Library for Neutrino Telescopes Event reconstruction for KM3NeT/ORCA using convolutional neural networks

Reference 8

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Observation ad1a61f4-9426-49e0-906e-935c6fd31d3f · outbound

This paper cites Observation of high-energy neutrinos from the galactic plane.

GraphNeT 2.0 -- A Deep Learning Library for Neutrino Telescopes Observation of high-energy neutrinos from the galactic plane

Reference 10

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Observation 55b726df-3488-4c7f-a664-7eaf442009b1 · outbound

This paper cites Søgaard, R.

GraphNeT 2.0 -- A Deep Learning Library for Neutrino Telescopes Søgaard, R

Reference 11

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Observation 89435cfd-a9be-4fe8-9c81-f15525af0632 · outbound

This paper cites PyTorch 2: Faster Machine Learning Through Dynamic Python Bytecode Transformation and Graph Compilation.

GraphNeT 2.0 -- A Deep Learning Library for Neutrino Telescopes PyTorch 2: Faster Machine Learning Through Dynamic Python Bytecode Transformation and Graph Compilation

Reference 12

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Observation 6ba013dd-5a5f-40b7-beb7-c16697061d46 · outbound

This paper cites Fey and J.

GraphNeT 2.0 -- A Deep Learning Library for Neutrino Telescopes Fey and J

Reference 13

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Observation 9fb82648-ecd5-4b39-8493-a2a51cd19243 · outbound

This paper cites Falcon and The PyTorch Lightning team,PyTorch Lightning, version 1.4, Mar.

GraphNeT 2.0 -- A Deep Learning Library for Neutrino Telescopes Falcon and The PyTorch Lightning team,PyTorch Lightning, version 1.4, Mar

Reference 14

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Observation b8e5b2f4-a452-40d0-83c4-b2645fecdb67 · outbound

This paper cites Langa and contributors to Black, Black: The uncompromising Python code formatter.

GraphNeT 2.0 -- A Deep Learning Library for Neutrino Telescopes Langa and contributors to Black, Black: The uncompromising Python code formatter

Reference 15

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Observation d304cb30-efb5-4c8a-a94c-b58ce6411636 · outbound

This paper cites Style guide for Python code.

GraphNeT 2.0 -- A Deep Learning Library for Neutrino Telescopes Style guide for Python code

Reference 16

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Observation 397b5b82-57ac-46d9-9345-068027d04707 · outbound

This paper cites GraphNeT: Graph neural networks for neutrino telescope event reconstruction.

GraphNeT 2.0 -- A Deep Learning Library for Neutrino Telescopes GraphNeT: Graph neural networks for neutrino telescope event reconstruction

Reference 17

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Observation 15511c7e-6dcf-47a4-a638-13eb69eeed97 · outbound

This paper cites LiquidO: First Opaque Detector for ββ Decay?.

GraphNeT 2.0 -- A Deep Learning Library for Neutrino Telescopes LiquidO: First Opaque Detector for ββ Decay?

Reference 18

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Observation b512d7ac-7cc0-4160-bf66-f1d4fa981685 · outbound

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GraphNeT 2.0 -- A Deep Learning Library for Neutrino Telescopes Unresolved cited work

Reference 19

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Observation 7b9ceb18-2fb9-42de-814f-0552b84f5a7e · outbound

This paper cites Automatic differentiation in PyTorch.

GraphNeT 2.0 -- A Deep Learning Library for Neutrino Telescopes Automatic differentiation in PyTorch

Reference 20

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Observation f82da7ff-9a26-4e55-931c-53f6a6750c1a · outbound

This paper cites The SNO+ Experiment.

GraphNeT 2.0 -- A Deep Learning Library for Neutrino Telescopes The SNO+ Experiment

Reference 21

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Observation da9decb4-0036-437c-a322-8e1a13fc710e · outbound

This paper cites The MAGIC Telescope.

GraphNeT 2.0 -- A Deep Learning Library for Neutrino Telescopes The MAGIC Telescope

Reference 22

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Observation 02161a1e-01f5-4931-a9be-01fa2d7a41df · outbound

This paper cites The Cherenkov Telescope Array.

GraphNeT 2.0 -- A Deep Learning Library for Neutrino Telescopes The Cherenkov Telescope Array

Reference 23

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Observation e5e36878-49a8-4573-8d5c-d03ef48566ce · outbound

This paper cites The European Spallation Source neutrino Super Beam Conceptual Design Report.

GraphNeT 2.0 -- A Deep Learning Library for Neutrino Telescopes The European Spallation Source neutrino Super Beam Conceptual Design Report

Reference 24

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Observation 94c8cdd4-d0d5-41da-b643-a492937b2150 · outbound

This paper cites Green, Deep learning for cherenkov event reconstruction, Talk presented at Erice, Slides available at: https://slides.com/astrojarred/green- jarred- erice- 2024 , Jul.

GraphNeT 2.0 -- A Deep Learning Library for Neutrino Telescopes Green, Deep learning for cherenkov event reconstruction, Talk presented at Erice, Slides available at: https://slides.com/astrojarred/green- jarred- erice- 2024 , Jul

Reference 25

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Observation c157bac9-c7d1-4d8b-b8f0-7eb409c7ab27 · outbound

This paper cites an unresolved cited work.

GraphNeT 2.0 -- A Deep Learning Library for Neutrino Telescopes Unresolved cited work

Reference 26

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation f20e0b07-72e3-4c6b-b382-6b8c63406f18 · outbound

This paper cites Wendel, Deep learning event reconstruction techniques for the cloud liquido based experi- ment, Poster presented at Neutrino2024, Available at: https://doi.org/10.5281/zenodo.

GraphNeT 2.0 -- A Deep Learning Library for Neutrino Telescopes Wendel, Deep learning event reconstruction techniques for the cloud liquido based experi- ment, Poster presented at Neutrino2024, Available at: https://doi.org/10.5281/zenodo

Reference 27

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Observation 39c3e95c-5d45-40c8-a172-8e5aadb2deb3 · outbound

This paper cites Graph neural networks for low-energy event classification & reconstruction in icecube.

GraphNeT 2.0 -- A Deep Learning Library for Neutrino Telescopes Graph neural networks for low-energy event classification & reconstruction in icecube

Reference 28

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Observation a2f236a6-6465-4631-ab0d-72ecf8161d92 · outbound

This paper cites Sensitivity of the IceCube Upgrade to Atmospheric Neutrino Oscillations.

GraphNeT 2.0 -- A Deep Learning Library for Neutrino Telescopes Sensitivity of the IceCube Upgrade to Atmospheric Neutrino Oscillations

Reference 29

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Observation fdc1307e-190b-4b87-86fd-216ee0ebb29f · outbound

This paper cites an unresolved cited work.

GraphNeT 2.0 -- A Deep Learning Library for Neutrino Telescopes Unresolved cited work

Reference 30

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Observation a5948be9-dc12-445b-a4f1-5f7d20da3a13 · outbound

This paper cites Public Kaggle Competition IceCube - Neutrinos in Deep ice.

GraphNeT 2.0 -- A Deep Learning Library for Neutrino Telescopes Public Kaggle Competition IceCube - Neutrinos in Deep ice

Reference 31

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doi, observed 2026-08-10T21:49:23.638096Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 8d8bc0e1-d007-46e1-988e-044938e29e54 · outbound

This paper cites Public Kaggle Competition "IceCube -- Neutrinos in Deep Ice".

GraphNeT 2.0 -- A Deep Learning Library for Neutrino Telescopes Public Kaggle Competition "IceCube -- Neutrinos in Deep Ice"

Reference 32

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local_arxiv, observed 2026-08-10T21:49:23.881006Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 128c645d-7ab7-4e76-9e95-234c5e8e98c0 · outbound

This paper cites Extending the IceCube search for neutrino point sources in the Northern sky with additional years of data.

GraphNeT 2.0 -- A Deep Learning Library for Neutrino Telescopes Extending the IceCube search for neutrino point sources in the Northern sky with additional years of data

Reference 33

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Observation d4cffd3d-b913-4a0e-94dd-0be0a595863b · outbound

This paper cites Prometheus: An open-source neutrino telescope simulation.

GraphNeT 2.0 -- A Deep Learning Library for Neutrino Telescopes Prometheus: An open-source neutrino telescope simulation

Reference 34

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raw_fallback, observed 2026-08-10T21:49:24.311983Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation dc3a8448-f47f-45ed-b45c-eb9e0c7d41f3 · outbound

This paper cites Improvement in Fast Particle Track Reconstruction with Robust Statistics.

GraphNeT 2.0 -- A Deep Learning Library for Neutrino Telescopes Improvement in Fast Particle Track Reconstruction with Robust Statistics

Reference 74

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no resolver link, observed 2026-08-10T21:49:23.434860Z

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Observation 56c95059-55b8-4618-afc6-239b19d8553f · outbound

This paper cites Combining Maximum-Likelihood with Deep Learning for Event Reconstruction in IceCube.

GraphNeT 2.0 -- A Deep Learning Library for Neutrino Telescopes Combining Maximum-Likelihood with Deep Learning for Event Reconstruction in IceCube

Reference 1065

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local_arxiv, observed 2026-08-10T21:49:24.102980Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation a8547eeb-5b37-4873-8aa3-28aee2ea36ae · outbound

This paper cites Available: https://github.com/pyg-team/pytorch_geometric.

GraphNeT 2.0 -- A Deep Learning Library for Neutrino Telescopes Available: https://github.com/pyg-team/pytorch_geometric

Reference 2019

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T21:49:24.456280Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation f1bd6102-6f89-46ba-bd4b-3fc59e4d6280 · outbound

This paper cites arXiv: 2304.14526 [hep-ex].

GraphNeT 2.0 -- A Deep Learning Library for Neutrino Telescopes arXiv: 2304.14526 [hep-ex]

Reference 2024

Resolution
unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Pith citing papers

No inbound Pith citation observations are available.