Paper Citation Record · LEDGER

Adaptive Collocation Point Strategies For Physics Informed Neural Networks via the QR Discrete Empirical Interpolation Method

As of 20 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 1 inbound Pith citation observation for arXiv:2501.07700.

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

pith.paper-citation-record.v1
2501.07700 v4

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T20:40:59.950549Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-03T02:29:11.422793Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T02:37:34.134519Z

Reference resolution

39 of 39 outbound references displayed

verified exact1
verified fuzzy35
unresolved3
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 95398225-48e9-4556-945c-092221d89e0b · outbound

This paper cites Physics-informed machine learning,.

Adaptive Collocation Point Strategies For Physics Informed Neural Networks via the QR Discrete Empirical Interpolation Method Physics-informed machine learning,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-10T20:40:59.778653Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 056aafde-db80-4f1f-b546-e101f9d70dd6 · outbound

This paper cites DeepXDE: A deep learning library for solving differential equations,.

Adaptive Collocation Point Strategies For Physics Informed Neural Networks via the QR Discrete Empirical Interpolation Method DeepXDE: A deep learning library for solving differential equations,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:41:00.583883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation fda9f14c-39ed-4579-b2db-7a084a853d54 · outbound

This paper cites Physics-informed neu- ral networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations,.

Adaptive Collocation Point Strategies For Physics Informed Neural Networks via the QR Discrete Empirical Interpolation Method Physics-informed neu- ral networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:41:00.567743Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4694a78c-324d-402c-84da-02cf571a0553 · outbound

This paper cites Physics- informed neural networks (PINNs) for fluid mechanics: A review,.

Adaptive Collocation Point Strategies For Physics Informed Neural Networks via the QR Discrete Empirical Interpolation Method Physics- informed neural networks (PINNs) for fluid mechanics: A review,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-10T20:40:59.793102Z

Source-reported events for the cited work

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Observation 4c4a86ed-dbc2-4525-9e52-9ac30d05cb67 · outbound

This paper cites Multiphysics- informed neural networks for coupled soil hydrothermal modeling,.

Adaptive Collocation Point Strategies For Physics Informed Neural Networks via the QR Discrete Empirical Interpolation Method Multiphysics- informed neural networks for coupled soil hydrothermal modeling,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:41:00.541627Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation af5b6f71-e9bb-4b31-ab13-bc60d5840166 · outbound

This paper cites 3D multi-physics uncertainty quantification using physics-based machine learning,.

Adaptive Collocation Point Strategies For Physics Informed Neural Networks via the QR Discrete Empirical Interpolation Method 3D multi-physics uncertainty quantification using physics-based machine learning,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:41:00.526456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e58d4cc0-7903-46da-8e0e-017a7e72bc80 · outbound

This paper cites Systems biology informed deep learning for inferring parameters and hidden dynamics,.

Adaptive Collocation Point Strategies For Physics Informed Neural Networks via the QR Discrete Empirical Interpolation Method Systems biology informed deep learning for inferring parameters and hidden dynamics,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:41:00.511202Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a1b70bb9-7bea-42db-adcd-9a86a5082dcd · outbound

This paper cites A comprehensive study of non-adaptive and residual-based adaptive sampling for physics- informed neural networks,.

Adaptive Collocation Point Strategies For Physics Informed Neural Networks via the QR Discrete Empirical Interpolation Method A comprehensive study of non-adaptive and residual-based adaptive sampling for physics- informed neural networks,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:41:00.496633Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 61cf1afd-688f-4989-80ab-1569a9750174 · outbound

This paper cites Meta-learning PINN loss functions,.

Adaptive Collocation Point Strategies For Physics Informed Neural Networks via the QR Discrete Empirical Interpolation Method Meta-learning PINN loss functions,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:41:00.481040Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d44f4436-3b34-41c9-82c2-609e3a395f76 · outbound

This paper cites Gradient-enhanced physics-informed neural networks for forward and inverse PDE prob- lems,.

Adaptive Collocation Point Strategies For Physics Informed Neural Networks via the QR Discrete Empirical Interpolation Method Gradient-enhanced physics-informed neural networks for forward and inverse PDE prob- lems,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:41:00.465713Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation af397fab-d7ec-4752-92d3-935d9b2cec82 · outbound

This paper cites NAS-PINN: neural architecture search- guided physics-informed neural network for solving PDEs,.

Adaptive Collocation Point Strategies For Physics Informed Neural Networks via the QR Discrete Empirical Interpolation Method NAS-PINN: neural architecture search- guided physics-informed neural network for solving PDEs,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:41:00.450367Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f265b0ba-a37c-4321-8589-bad87ef001a0 · outbound

This paper cites Physics-informed neural networks with hard constraints for inverse de- sign,.

Adaptive Collocation Point Strategies For Physics Informed Neural Networks via the QR Discrete Empirical Interpolation Method Physics-informed neural networks with hard constraints for inverse de- sign,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:41:00.435679Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 78e96417-b7c3-43ca-8bbb-8aa3c28b1afd · outbound

This paper cites fPINNs: Fractional physics- informed neural networks,.

Adaptive Collocation Point Strategies For Physics Informed Neural Networks via the QR Discrete Empirical Interpolation Method fPINNs: Fractional physics- informed neural networks,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:41:00.420052Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation cf40274f-942f-4be8-96f0-21e3e1c5a739 · outbound

This paper cites Adaptive deep neural networks methods for high-dimensional partial differential equations,.

Adaptive Collocation Point Strategies For Physics Informed Neural Networks via the QR Discrete Empirical Interpolation Method Adaptive deep neural networks methods for high-dimensional partial differential equations,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:41:00.405799Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ea69b297-8f4e-46bd-a296-b487a026d0f4 · outbound

This paper cites Residual-based adaptivity for two-phase flow simulation in porous media using physics-informed neural networks,.

Adaptive Collocation Point Strategies For Physics Informed Neural Networks via the QR Discrete Empirical Interpolation Method Residual-based adaptivity for two-phase flow simulation in porous media using physics-informed neural networks,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:41:00.391633Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9704b257-72ba-432b-9afb-b7bca42fc918 · outbound

This paper cites Efficient train- ing of physics-informed neural networks via importance sampling,.

Adaptive Collocation Point Strategies For Physics Informed Neural Networks via the QR Discrete Empirical Interpolation Method Efficient train- ing of physics-informed neural networks via importance sampling,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:41:00.376024Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 430c497a-0439-4cde-800a-40581b555d79 · outbound

This paper cites Investigating molecular transport in the human brain from MRI with physics-informed neural networks,.

Adaptive Collocation Point Strategies For Physics Informed Neural Networks via the QR Discrete Empirical Interpolation Method Investigating molecular transport in the human brain from MRI with physics-informed neural networks,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:41:00.361557Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ac42152e-8565-48f5-8929-129c4237ad31 · outbound

This paper cites Active learning based sampling for high- dimensional nonlinear partial differential equations,.

Adaptive Collocation Point Strategies For Physics Informed Neural Networks via the QR Discrete Empirical Interpolation Method Active learning based sampling for high- dimensional nonlinear partial differential equations,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:41:00.346228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 732e8dac-8c05-44b7-a053-da3894e66a13 · outbound

This paper cites Miti- gating propagation failures in physics-informed neural networks us- ing retain-resample-release (R3) sampling,.

Adaptive Collocation Point Strategies For Physics Informed Neural Networks via the QR Discrete Empirical Interpolation Method Miti- gating propagation failures in physics-informed neural networks us- ing retain-resample-release (R3) sampling,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:41:00.330007Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2c399edb-98e0-4672-bb4f-214d9f4fd6e6 · outbound

This paper cites PIN- NACLE: PINN adaptive collocation and experimental points selection,.

Adaptive Collocation Point Strategies For Physics Informed Neural Networks via the QR Discrete Empirical Interpolation Method PIN- NACLE: PINN adaptive collocation and experimental points selection,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:41:00.314203Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 47cec172-c71d-4ef1-b51b-d1106007bd10 · outbound

This paper cites Nonlinear model reduc- tion via discrete empirical interpolation,.

Adaptive Collocation Point Strategies For Physics Informed Neural Networks via the QR Discrete Empirical Interpolation Method Nonlinear model reduc- tion via discrete empirical interpolation,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:41:00.298340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 01114c13-a8d6-4753-b11b-e75144bb1ca5 · outbound

This paper cites A new selection operator for the discrete em- pirical interpolation method—improved a priori error bound and exten- sions,.

Adaptive Collocation Point Strategies For Physics Informed Neural Networks via the QR Discrete Empirical Interpolation Method A new selection operator for the discrete em- pirical interpolation method—improved a priori error bound and exten- sions,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:41:00.281396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4677de0c-5630-481e-92a2-d727cc4073c4 · outbound

This paper cites GS-PINN: Greedy Sampling for Parameter Estimation in Partial Differential Equations.

Adaptive Collocation Point Strategies For Physics Informed Neural Networks via the QR Discrete Empirical Interpolation Method GS-PINN: Greedy Sampling for Parameter Estimation in Partial Differential Equations

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-08-10T20:40:59.993994Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 22a660f6-8c0a-4e80-a53a-a9e9d34eedad · outbound

This paper cites Projection methods for reduced order mod- els of compressible flows,.

Adaptive Collocation Point Strategies For Physics Informed Neural Networks via the QR Discrete Empirical Interpolation Method Projection methods for reduced order mod- els of compressible flows,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:41:00.264542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation bedc2999-790c-415a-a399-25628c2908bf · outbound

This paper cites Stabilization of projection-based reduced- order models,.

Adaptive Collocation Point Strategies For Physics Informed Neural Networks via the QR Discrete Empirical Interpolation Method Stabilization of projection-based reduced- order models,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:41:00.246612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b2019bff-ea88-49ca-accc-766d6ea6f197 · outbound

This paper cites On projection- based algorithms for model-order reduction of interconnects,.

Adaptive Collocation Point Strategies For Physics Informed Neural Networks via the QR Discrete Empirical Interpolation Method On projection- based algorithms for model-order reduction of interconnects,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:41:00.230776Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 89bdddcc-ce85-4303-9844-02e634a5085a · outbound

This paper cites Proper orthogonal decomposition extensions for parametric applications in compressible aerodynamics,.

Adaptive Collocation Point Strategies For Physics Informed Neural Networks via the QR Discrete Empirical Interpolation Method Proper orthogonal decomposition extensions for parametric applications in compressible aerodynamics,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:41:00.215441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7e6b68f3-a99b-41c8-9bd2-fba456e03beb · outbound

This paper cites The proper orthogonal de- composition in the analysis of turbulent flows,.

Adaptive Collocation Point Strategies For Physics Informed Neural Networks via the QR Discrete Empirical Interpolation Method The proper orthogonal de- composition in the analysis of turbulent flows,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:41:00.197862Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1d72968e-0cba-4b13-8333-a4d01bfbb3f5 · outbound

This paper cites A reduced-order approach for optimal control of flu- ids using proper orthogonal decomposition,.

Adaptive Collocation Point Strategies For Physics Informed Neural Networks via the QR Discrete Empirical Interpolation Method A reduced-order approach for optimal control of flu- ids using proper orthogonal decomposition,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:41:00.181451Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 69537d96-e037-40e3-81e4-40f2dea024c0 · outbound

This paper cites Proper orthogonal decomposition for linear-quadratic optimal control,.

Adaptive Collocation Point Strategies For Physics Informed Neural Networks via the QR Discrete Empirical Interpolation Method Proper orthogonal decomposition for linear-quadratic optimal control,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:41:00.165294Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c32cc432-fc58-4730-828c-64bc5f65ca32 · outbound

This paper cites Nonlinear model order reduction via lifting transformations and proper orthogonal decomposition,.

Adaptive Collocation Point Strategies For Physics Informed Neural Networks via the QR Discrete Empirical Interpolation Method Nonlinear model order reduction via lifting transformations and proper orthogonal decomposition,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:41:00.148589Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 6cc2b6da-9f3f-4711-ae42-6003a8234561 · outbound

This paper cites Discrete empirical interpola- tion for nonlinear model reduction,.

Adaptive Collocation Point Strategies For Physics Informed Neural Networks via the QR Discrete Empirical Interpolation Method Discrete empirical interpola- tion for nonlinear model reduction,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:41:00.132939Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d0bf262c-3c4d-4355-818a-c3c7349530f7 · outbound

This paper cites Finding structure with randomness: Probabilistic algorithms for constructing approximate ma- trix decompositions,.

Adaptive Collocation Point Strategies For Physics Informed Neural Networks via the QR Discrete Empirical Interpolation Method Finding structure with randomness: Probabilistic algorithms for constructing approximate ma- trix decompositions,

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-10T20:40:59.923192Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6d7e7bbc-c2e7-424e-a4fd-2ba72185b055 · outbound

This paper cites Challenges in training pinns: a loss landscape perspective,.

Adaptive Collocation Point Strategies For Physics Informed Neural Networks via the QR Discrete Empirical Interpolation Method Challenges in training pinns: a loss landscape perspective,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:41:00.106263Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 0bd281bb-dbe4-4e79-aff2-b915799b4ead · outbound

This paper cites Characterizing possible failure modes in physics-informed neural net- works,.

Adaptive Collocation Point Strategies For Physics Informed Neural Networks via the QR Discrete Empirical Interpolation Method Characterizing possible failure modes in physics-informed neural net- works,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:41:00.089549Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1371866a-1adb-464d-b282-aa4ce62ffc38 · outbound

This paper cites Kolmogorov n– width and lagrangian physics-informed neural networks: A causality- conforming manifold for convection-dominated pdes,.

Adaptive Collocation Point Strategies For Physics Informed Neural Networks via the QR Discrete Empirical Interpolation Method Kolmogorov n– width and lagrangian physics-informed neural networks: A causality- conforming manifold for convection-dominated pdes,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:41:00.072860Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d8fff5fa-8dbf-42a8-a313-1b168e923aeb · outbound

This paper cites A unified scalable framework for causal sweeping strategies for physics-informed neural networks (pinns) and their temporal decompo- sitions,.

Adaptive Collocation Point Strategies For Physics Informed Neural Networks via the QR Discrete Empirical Interpolation Method A unified scalable framework for causal sweeping strategies for physics-informed neural networks (pinns) and their temporal decompo- sitions,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:41:00.056788Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7270da50-18b6-4053-9ddb-aed93a827074 · outbound

This paper cites Extended physics-informed neu- ral networks (xpinns): A generalized space-time domain decomposition based deep learning framework for nonlinear partial differential equa- tions,.

Adaptive Collocation Point Strategies For Physics Informed Neural Networks via the QR Discrete Empirical Interpolation Method Extended physics-informed neu- ral networks (xpinns): A generalized space-time domain decomposition based deep learning framework for nonlinear partial differential equa- tions,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:41:00.039451Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 55b7be42-7b78-41a7-ab4e-72a9212ea0ea · outbound

This paper cites Solving Allen-Cahn and Cahn-Hilliard Equations using the Adaptive Physics Informed Neural Networks,.

Adaptive Collocation Point Strategies For Physics Informed Neural Networks via the QR Discrete Empirical Interpolation Method Solving Allen-Cahn and Cahn-Hilliard Equations using the Adaptive Physics Informed Neural Networks,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:41:00.020812Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Pith citing papers

Observation e87b82a6-7e06-4775-98eb-86b704ee5515 · inbound

Identifiability Limits of Physics-Informed Inference for Spatial Stochastic Dynamics from Static Snapshots cites this paper.

Identifiability Limits of Physics-Informed Inference for Spatial Stochastic Dynamics from Static Snapshots Adaptive Collocation Point Strategies For Physics Informed Neural Networks via the QR Discrete Empirical Interpolation Method

Reference 45

Resolution: verified exact; arxiv_id, observed 2026-07-03T02:37:34.136210Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.