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Paper Citation Record · LEDGER

GRIT: Graph Transformer For Internal Ice Layer Thickness Prediction

As of 8 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 0 inbound Pith citation observations for arXiv:2507.07388.

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

pith.paper-citation-record.v1
2507.07388 v1

Coverage vector

measured 22 of 22 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:46:00.340987Z

measured 22 of 22 standing notices

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

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Reference resolution

22 of 22 outbound references displayed

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External citation measurements

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Outbound references

Observation 1e0241ec-45bc-41e6-bdb9-b914666beba8 · outbound

This paper cites Chapter 12 - glaciers and ice sheets,.

GRIT: Graph Transformer For Internal Ice Layer Thickness Prediction Chapter 12 - glaciers and ice sheets,

Reference 1

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Observation 8ba572ec-f6bd-4f37-9bcb-9ce90027ec83 · outbound

This paper cites Cresis airborne radars and platforms for ice and snow sounding,.

GRIT: Graph Transformer For Internal Ice Layer Thickness Prediction Cresis airborne radars and platforms for ice and snow sounding,

Reference 3

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Observation 97002525-0a36-45fb-acfa-1033129a704d · outbound

This paper cites Prediction of deep ice layer thickness using adaptive recurrent graph neural networks,.

GRIT: Graph Transformer For Internal Ice Layer Thickness Prediction Prediction of deep ice layer thickness using adaptive recurrent graph neural networks,

Reference 4

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Observation bdc8dd88-1e20-423f-85e6-575b679f7126 · outbound

This paper cites Prediction of annual snow accumulation using a recur- rent graph convolutional approach,.

GRIT: Graph Transformer For Internal Ice Layer Thickness Prediction Prediction of annual snow accumulation using a recur- rent graph convolutional approach,

Reference 5

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Observation 5ec3ec7f-a77f-404e-a894-a6be231f66f6 · outbound

This paper cites Recurrent graph convolutional networks for spatiotem- poral prediction of snow accumulation using airborne radar,.

GRIT: Graph Transformer For Internal Ice Layer Thickness Prediction Recurrent graph convolutional networks for spatiotem- poral prediction of snow accumulation using airborne radar,

Reference 6

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Observation 653e63a0-5f30-46bd-a39b-42620378e57f · outbound

This paper cites Learning spatio-temporal patterns of polar ice layers with physics-informed graph neural network,.

GRIT: Graph Transformer For Internal Ice Layer Thickness Prediction Learning spatio-temporal patterns of polar ice layers with physics-informed graph neural network,

Reference 7

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Observation 9386960f-1e53-4b54-b3ed-f2cbc2da48de · outbound

This paper cites Multi-branch Spatio-Temporal Graph Neural Network For Efficient Ice Layer Thickness Prediction.

GRIT: Graph Transformer For Internal Ice Layer Thickness Prediction Multi-branch Spatio-Temporal Graph Neural Network For Efficient Ice Layer Thickness Prediction

Reference 8

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Observation 031d4375-c814-47f6-9ab8-669c9577f526 · outbound

This paper cites Physics-informed machine learning for deep ice layer tracing in sar images,.

GRIT: Graph Transformer For Internal Ice Layer Thickness Prediction Physics-informed machine learning for deep ice layer tracing in sar images,

Reference 9

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Observation 671b23e9-fe6b-4e43-a9af-bc2101925e88 · outbound

This paper cites Learning snow layer thickness through physics defined labels,.

GRIT: Graph Transformer For Internal Ice Layer Thickness Prediction Learning snow layer thickness through physics defined labels,

Reference 10

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

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Observation e5384606-a0d5-409e-8a42-e2e420ef2e72 · outbound

This paper cites Deep ice layer tracking and thickness estimation using fully convo- lutional networks,.

GRIT: Graph Transformer For Internal Ice Layer Thickness Prediction Deep ice layer tracking and thickness estimation using fully convo- lutional networks,

Reference 11

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Observation dde399e4-d966-4dba-a160-e63673b235cb · outbound

This paper cites Deep learning on airborne radar echograms for tracing snow accumulation layers of the greenland ice sheet,.

GRIT: Graph Transformer For Internal Ice Layer Thickness Prediction Deep learning on airborne radar echograms for tracing snow accumulation layers of the greenland ice sheet,

Reference 12

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Observation 6c60c5d6-2dfc-4071-a640-6ef8c8624745 · outbound

This paper cites Deep multi-scale learning for automatic tracking of internal layers of ice in radar data,.

GRIT: Graph Transformer For Internal Ice Layer Thickness Prediction Deep multi-scale learning for automatic tracking of internal layers of ice in radar data,

Reference 13

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Observation 2da2dc24-7b7b-40ac-8670-85a49fc13e38 · outbound

This paper cites Airborne snow radar data simulation with deep learning and physics-driven methods,.

GRIT: Graph Transformer For Internal Ice Layer Thickness Prediction Airborne snow radar data simulation with deep learning and physics-driven methods,

Reference 14

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Observation 8975c794-5d24-4f8a-9173-79847c947a25 · outbound

This paper cites Deep hybrid wavelet network for ice boundary de- tection in radra imagery,.

GRIT: Graph Transformer For Internal Ice Layer Thickness Prediction Deep hybrid wavelet network for ice boundary de- tection in radra imagery,

Reference 15

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Observation 4442289e-cb32-4f02-aba7-5e2ed29825a3 · outbound

This paper cites Refining ice layer tracking through wavelet combined neural networks,.

GRIT: Graph Transformer For Internal Ice Layer Thickness Prediction Refining ice layer tracking through wavelet combined neural networks,

Reference 16

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Observation 34c64093-8889-4748-b935-fef614848889 · outbound

This paper cites EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs.

GRIT: Graph Transformer For Internal Ice Layer Thickness Prediction EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs

Reference 17

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Observation fb0f255e-2815-4152-98e5-21f3d61fae0a · outbound

This paper cites Ultra-wideband radars for remote sensing of snow and ice,.

GRIT: Graph Transformer For Internal Ice Layer Thickness Prediction Ultra-wideband radars for remote sensing of snow and ice,

Reference 18

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Observation c5b18643-aff6-44d8-9e41-163a7e79ff37 · outbound

This paper cites Icebridge snow radar l1b geolocated radar echo strength profiles,.

GRIT: Graph Transformer For Internal Ice Layer Thickness Prediction Icebridge snow radar l1b geolocated radar echo strength profiles,

Reference 19

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Observation 56a4018a-4393-4316-9fb5-e3b5ffd0c3b6 · outbound

This paper cites Semi-Supervised Classification with Graph Convolutional Networks.

GRIT: Graph Transformer For Internal Ice Layer Thickness Prediction Semi-Supervised Classification with Graph Convolutional Networks

Reference 20

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Observation 17b88142-4e54-4879-b49c-5062bc9a4af9 · outbound

This paper cites Inductive represen- tation learning on large graphs,.

GRIT: Graph Transformer For Internal Ice Layer Thickness Prediction Inductive represen- tation learning on large graphs,

Reference 21

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Observation d05a6d32-2cdf-43b1-91aa-b205e8b7e847 · outbound

This paper cites Graph neural networks: A review of methods and applications,.

GRIT: Graph Transformer For Internal Ice Layer Thickness Prediction Graph neural networks: A review of methods and applications,

Reference 22

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Observation 1ed02209-b42d-4a2e-bfb6-87804eae3b70 · outbound

This paper cites Attention is all you need,.

GRIT: Graph Transformer For Internal Ice Layer Thickness Prediction Attention is all you need,

Reference 23

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Pith citing papers

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