Paper Citation Record · LEDGER

Kernel-learning parameter prediction and evaluation in algebraic multigrid method for several PDEs

As of 21 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2504.14930.

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Outbound references

Observation 4c1953bf-5014-4ada-a60d-61ba62483dd0 · outbound

This paper cites Accelerating algebraic multigrid methods via artificial neural networks.

Kernel-learning parameter prediction and evaluation in algebraic multigrid method for several PDEs Accelerating algebraic multigrid methods via artificial neural networks

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:41:40.972708Z

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Observation 4de47a27-3d3a-4c55-8898-4ed827810fcf · outbound

This paper cites Algebraic multigrid schemes for high-order nodal discontinuous Galerkin methods.

Kernel-learning parameter prediction and evaluation in algebraic multigrid method for several PDEs Algebraic multigrid schemes for high-order nodal discontinuous Galerkin methods

Reference 2

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Observation c497719d-6ada-4dd9-907e-0a9fbc4afd8c · outbound

This paper cites iFEM: an innovative finite element methods package in MATLAB.

Kernel-learning parameter prediction and evaluation in algebraic multigrid method for several PDEs iFEM: an innovative finite element methods package in MATLAB

Reference 3

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Observation 728d6906-692f-4a63-9e7f-875448a4afb6 · outbound

This paper cites Gaussian processes for machine learning.

Kernel-learning parameter prediction and evaluation in algebraic multigrid method for several PDEs Gaussian processes for machine learning

Reference 4

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Observation 29b092b2-4e48-4ea2-837d-ea71c0002d13 · outbound

This paper cites hypre: A library of high performance preconditioners.

Kernel-learning parameter prediction and evaluation in algebraic multigrid method for several PDEs hypre: A library of high performance preconditioners

Reference 5

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Observation 2dd1eec5-1e84-4780-9740-aacd6fb3c430 · outbound

This paper cites Limitations of Bayesian leave-one-out cross-validation for model selection.

Kernel-learning parameter prediction and evaluation in algebraic multigrid method for several PDEs Limitations of Bayesian leave-one-out cross-validation for model selection

Reference 6

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Observation a1729acc-74bd-4674-9d20-3d5dd718fbdf · outbound

This paper cites Coarsening in algebraic multigrid using Gaussian processes.

Kernel-learning parameter prediction and evaluation in algebraic multigrid method for several PDEs Coarsening in algebraic multigrid using Gaussian processes

Reference 7

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Observation 96175272-6e79-4265-ae8d-69783c9f7e96 · outbound

This paper cites FP-AMG: FPGA-based acceleration frame- work for algebraic multigrid solvers.

Kernel-learning parameter prediction and evaluation in algebraic multigrid method for several PDEs FP-AMG: FPGA-based acceleration frame- work for algebraic multigrid solvers

Reference 8

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Observation 5affbc52-2ee5-4d71-8cc2-a2f6784a2933 · outbound

This paper cites Root mean square error (RMSE) or mean absolute error (MAE): When to use them or not.

Kernel-learning parameter prediction and evaluation in algebraic multigrid method for several PDEs Root mean square error (RMSE) or mean absolute error (MAE): When to use them or not

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:41:40.848754Z

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Observation 16d828fa-e325-4d91-99be-089f62e8606a · outbound

This paper cites A general alternating-direction implicit framework with Gaussian process regression parameter prediction for large sparse linear systems.

Kernel-learning parameter prediction and evaluation in algebraic multigrid method for several PDEs A general alternating-direction implicit framework with Gaussian process regression parameter prediction for large sparse linear systems

Reference 10

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Observation e67da7b3-f115-4238-b7aa-801ba96fb7b6 · outbound

This paper cites Multitask kernel-learning parameter prediction method for solv- ing time-dependent linear systems.

Kernel-learning parameter prediction and evaluation in algebraic multigrid method for several PDEs Multitask kernel-learning parameter prediction method for solv- ing time-dependent linear systems

Reference 11

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Observation e9037069-3658-41a2-ae95-dd3f143d068b · outbound

This paper cites Algebraic multi-grid for discrete elliptic second-order problems.

Kernel-learning parameter prediction and evaluation in algebraic multigrid method for several PDEs Algebraic multi-grid for discrete elliptic second-order problems

Reference 12

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Observation 7723531f-4837-4b65-bb59-83f822d9f9d3 · outbound

This paper cites Algebraic multigrid.

Kernel-learning parameter prediction and evaluation in algebraic multigrid method for several PDEs Algebraic multigrid

Reference 13

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Observation 928d9ad1-6f7c-4a51-9722-255dd47f6169 · outbound

This paper cites GPU acceleration of algebraic multigrid preconditioners for discrete elliptic field problems.

Kernel-learning parameter prediction and evaluation in algebraic multigrid method for several PDEs GPU acceleration of algebraic multigrid preconditioners for discrete elliptic field problems

Reference 14

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Observation bc535760-b1c1-4b98-a148-8c0bffdd07b5 · outbound

This paper cites Learning algebraic multigrid using graph neu- ral networks.

Kernel-learning parameter prediction and evaluation in algebraic multigrid method for several PDEs Learning algebraic multigrid using graph neu- ral networks

Reference 15

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Observation 2e0b2ee9-5cf6-4599-a54b-729cc52f1171 · outbound

This paper cites Adaptive algebraic multigrid.

Kernel-learning parameter prediction and evaluation in algebraic multigrid method for several PDEs Adaptive algebraic multigrid

Reference 16

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Observation 92365328-184d-4e66-ad11-44460c27c8aa · outbound

This paper cites The Bayesian information criterion: background, derivation, and applications.

Kernel-learning parameter prediction and evaluation in algebraic multigrid method for several PDEs The Bayesian information criterion: background, derivation, and applications

Reference 17

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Observation 500724ef-c2a0-402b-840c-dfc05a32dd41 · outbound

This paper cites Algebraic multigrid for discontinuous Galerkin discretizations of heterogeneous elliptic problems.

Kernel-learning parameter prediction and evaluation in algebraic multigrid method for several PDEs Algebraic multigrid for discontinuous Galerkin discretizations of heterogeneous elliptic problems

Reference 18

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Observation 1136e62b-93cd-4c5d-bfd5-1942ddf36d09 · outbound

This paper cites Parameter selection in Gaussian process interpolation: an empirical study of selection criteria.

Kernel-learning parameter prediction and evaluation in algebraic multigrid method for several PDEs Parameter selection in Gaussian process interpolation: an empirical study of selection criteria

Reference 19

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Observation 5cfd0db7-48bf-4e52-8d8a-246aad39fb9c · outbound

This paper cites A scalable estimate of the out-of-sample prediction error via approxi- mate leave-one-out cross-validation.

Kernel-learning parameter prediction and evaluation in algebraic multigrid method for several PDEs A scalable estimate of the out-of-sample prediction error via approxi- mate leave-one-out cross-validation

Reference 20

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Observation b20dbe64-22c7-41f9-8dda-9df21867ca77 · outbound

This paper cites & Bui D T.

Kernel-learning parameter prediction and evaluation in algebraic multigrid method for several PDEs & Bui D T

Reference 21

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Observation 1fd44bc1-a98b-43fb-a9ed-27c30e20b04a · outbound

This paper cites Robust Gaussian process modeling using EM algorithm.

Kernel-learning parameter prediction and evaluation in algebraic multigrid method for several PDEs Robust Gaussian process modeling using EM algorithm

Reference 22

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Observation a806739a-a57a-416b-b186-31fa8b0f5c87 · outbound

This paper cites On solving groundwater flow and transport models with algebraic 23 multigrid preconditioning.

Kernel-learning parameter prediction and evaluation in algebraic multigrid method for several PDEs On solving groundwater flow and transport models with algebraic 23 multigrid preconditioning

Reference 23

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Observation c7f9c4c5-da58-4afb-8f13-c6025096f7fb · outbound

This paper cites A tutorial on Gaussian process regression: Modelling, exploring, and exploiting functions.

Kernel-learning parameter prediction and evaluation in algebraic multigrid method for several PDEs A tutorial on Gaussian process regression: Modelling, exploring, and exploiting functions

Reference 24

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Observation 3241feb5-8765-4916-ae21-cf278800537d · outbound

This paper cites Machine learning approaches for estimation of prediction interval for the model output.

Kernel-learning parameter prediction and evaluation in algebraic multigrid method for several PDEs Machine learning approaches for estimation of prediction interval for the model output

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:41:40.594794Z

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Observation 9ff1248b-5796-400b-9ebe-8837b0416f35 · outbound

This paper cites Optimization-based algebraic multigrid coarsening using reinforcement learning.

Kernel-learning parameter prediction and evaluation in algebraic multigrid method for several PDEs Optimization-based algebraic multigrid coarsening using reinforcement learning

Reference 26

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Observation cc1b23d6-ba5f-433c-bb81-226da6d6af30 · outbound

This paper cites Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC.

Kernel-learning parameter prediction and evaluation in algebraic multigrid method for several PDEs Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC

Reference 27

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Observation 47febaf7-cb13-4050-903a-3e2766d24649 · outbound

This paper cites A widely applicable Bayesian information criterion.

Kernel-learning parameter prediction and evaluation in algebraic multigrid method for several PDEs A widely applicable Bayesian information criterion

Reference 28

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Observation 2a8e6df1-9455-4363-9bfb-069411d7202a · outbound

This paper cites Algebraic multigrid methods for saddle point systems arising from mortar contact formulations.

Kernel-learning parameter prediction and evaluation in algebraic multigrid method for several PDEs Algebraic multigrid methods for saddle point systems arising from mortar contact formulations

Reference 29

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Observation f497965c-5318-4a4b-b911-aca3e795cdd4 · outbound

This paper cites & Huang M.

Kernel-learning parameter prediction and evaluation in algebraic multigrid method for several PDEs & Huang M

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:41:40.513508Z

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Observation ffc744b7-2f4a-494f-94d9-44c21c3bf379 · outbound

This paper cites An aggregation-based algebraic multigrid method.

Kernel-learning parameter prediction and evaluation in algebraic multigrid method for several PDEs An aggregation-based algebraic multigrid method

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:41:40.495170Z

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Observation 32f4f22b-bdc9-4f49-829e-083227d4363e · outbound

This paper cites A supplementary strategy for coarsening in algebraic multigrid.

Kernel-learning parameter prediction and evaluation in algebraic multigrid method for several PDEs A supplementary strategy for coarsening in algebraic multigrid

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:41:40.477499Z

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Observation f4d30a1d-e316-46df-bf6c-1241ebb043bc · outbound

This paper cites Gaussian process regression-based load forecasting model.

Kernel-learning parameter prediction and evaluation in algebraic multigrid method for several PDEs Gaussian process regression-based load forecasting model

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:41:40.460886Z

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Observation ec413b4c-56db-42d4-b1d1-238fa4880aae · outbound

This paper cites AutoAMG (θ): An Auto-tuned AMG Method Based on Deep Learning for Strong Threshold.

Kernel-learning parameter prediction and evaluation in algebraic multigrid method for several PDEs AutoAMG (θ): An Auto-tuned AMG Method Based on Deep Learning for Strong Threshold

Reference 34

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