Paper Citation Record · LEDGER

IP-Basis PINNs: Efficient Multi-Query Inverse Parameter Estimation

As of 17 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:2509.07245.

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

pith.paper-citation-record.v1
2509.07245 v1

Coverage vector

measured 41 of 41 reference resolution

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Source: paper_references, paper_reference_links, observed 2026-08-04T22:39:13.745212Z

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Pith citing papers itemized under the disclosed page cap.

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

Source: cited_works

Reference resolution

41 of 41 outbound references displayed

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verified fuzzy13
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External citation measurements

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Outbound references

Observation fb8c7ac6-fbb2-4978-94dd-7e600f72b7a5 · outbound

This paper cites GPT-PINN: Generative Pre-Trained Physics-Informed Neural Net- works toward non-intrusive Meta-learning of parametric PDEs.

IP-Basis PINNs: Efficient Multi-Query Inverse Parameter Estimation GPT-PINN: Generative Pre-Trained Physics-Informed Neural Net- works toward non-intrusive Meta-learning of parametric PDEs

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:39:14.686580Z

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Observation 53075d6c-ac96-474e-9315-f1f5cd5113e3 · outbound

This paper cites Advanced Physics-informed neural networks for numerical approximation of the coupled Schr¨ odinger–KdV equation.

IP-Basis PINNs: Efficient Multi-Query Inverse Parameter Estimation Advanced Physics-informed neural networks for numerical approximation of the coupled Schr¨ odinger–KdV equation

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-04T22:39:13.445143Z

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Observation 640ae774-0bd6-4021-8252-bb623d3cbef0 · outbound

This paper cites Fiber transmission model with parameterized inputs based on generative pre-trained physics-informed neural networks.

IP-Basis PINNs: Efficient Multi-Query Inverse Parameter Estimation Fiber transmission model with parameterized inputs based on generative pre-trained physics-informed neural networks

Reference 3

Resolution: verified exact; doi, observed 2026-08-04T22:39:14.276189Z

Source-reported events for the cited work

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Observation 1d12e047-eaba-4c51-92b6-91937e520cfb · outbound

This paper cites A Comprehensive Survey on Transfer Learning.

IP-Basis PINNs: Efficient Multi-Query Inverse Parameter Estimation A Comprehensive Survey on Transfer Learning

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-04T22:39:13.461485Z

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Observation 42677c2b-809d-4c6c-a87f-f53f6d3d23a3 · outbound

This paper cites One-Shot Transfer Learning of Physics-Informed Neural Networks.

IP-Basis PINNs: Efficient Multi-Query Inverse Parameter Estimation One-Shot Transfer Learning of Physics-Informed Neural Networks

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-04T22:39:13.468798Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6fb8e918-dd7c-4a54-9b20-69386be8927b · outbound

This paper cites Meta-learning Loss Functions of Parametric Partial Differential Equations Using Physics-Informed Neural Networks.

IP-Basis PINNs: Efficient Multi-Query Inverse Parameter Estimation Meta-learning Loss Functions of Parametric Partial Differential Equations Using Physics-Informed Neural Networks

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-08-04T22:39:14.408893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 72f4a80e-c20c-4c4b-970d-2287418fd9ff · outbound

This paper cites Automatic Differentiation in Machine Learning: a Survey.

IP-Basis PINNs: Efficient Multi-Query Inverse Parameter Estimation Automatic Differentiation in Machine Learning: a Survey

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:39:14.666632Z

Source-reported events for the cited work

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Observation 7987f242-f539-4b5f-bd40-aac47f714879 · outbound

This paper cites PyTorch: An Imperative Style, High-Performance Deep Learning Library.

IP-Basis PINNs: Efficient Multi-Query Inverse Parameter Estimation PyTorch: An Imperative Style, High-Performance Deep Learning Library

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:39:14.649176Z

Source-reported events for the cited work

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Observation 53e5d43f-6151-4131-a401-37feb39e4a84 · outbound

This paper cites Software available from tensorflow.org.

IP-Basis PINNs: Efficient Multi-Query Inverse Parameter Estimation Software available from tensorflow.org

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:39:14.632088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 86b5b1f9-0271-4cc7-a909-aeb804535057 · outbound

This paper cites Second-Order Forward-Mode Automatic Differentiation for Optimization.

IP-Basis PINNs: Efficient Multi-Query Inverse Parameter Estimation Second-Order Forward-Mode Automatic Differentiation for Optimization

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-04T22:39:13.502128Z

Source-reported events for the cited work

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Observation 86973472-5d26-4d7e-ba27-779bf2506e7b · outbound

This paper cites Universal Physics-Informed Neural Net- works: Symbolic Differential Operator Discovery with Sparse Data.

IP-Basis PINNs: Efficient Multi-Query Inverse Parameter Estimation Universal Physics-Informed Neural Net- works: Symbolic Differential Operator Discovery with Sparse Data

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:39:14.614619Z

Source-reported events for the cited work

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Observation 30d0d0f0-18a7-4d22-b546-a3107a5bddc8 · outbound

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

IP-Basis PINNs: Efficient Multi-Query Inverse Parameter Estimation Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

Reference 12

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Source-reported events for the cited work

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Observation c2d3eecf-ad1a-4173-bff0-edd5548c5f08 · outbound

This paper cites Baratta et al.DOLFINx: the next generation FEniCS problem solving environment.

IP-Basis PINNs: Efficient Multi-Query Inverse Parameter Estimation Baratta et al.DOLFINx: the next generation FEniCS problem solving environment

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-04T22:39:13.522287Z

Source-reported events for the cited work

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Observation 838b0136-7c6c-42e4-b60e-7538f2965d6c · outbound

This paper cites A Survey of Projection-Based Model Reduction Methods for Parametric Dynamical Systems.

IP-Basis PINNs: Efficient Multi-Query Inverse Parameter Estimation A Survey of Projection-Based Model Reduction Methods for Parametric Dynamical Systems

Reference 14

Resolution: verified exact; doi, observed 2026-08-04T22:39:14.163967Z

Source-reported events for the cited work

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Observation 4afa2e82-6cdd-455a-a054-13002d8c160b · outbound

This paper cites The”echo state.

IP-Basis PINNs: Efficient Multi-Query Inverse Parameter Estimation The”echo state

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:39:14.597335Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 50b1b023-ba26-4c8a-bf7d-aeadc83e2ae4 · outbound

This paper cites Next generation reservoir computing.

IP-Basis PINNs: Efficient Multi-Query Inverse Parameter Estimation Next generation reservoir computing

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:39:14.575609Z

Source-reported events for the cited work

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Observation b7b1b917-fe16-4be9-9606-029aa88dc70f · outbound

This paper cites Task-adaptive physical reservoir computing.

IP-Basis PINNs: Efficient Multi-Query Inverse Parameter Estimation Task-adaptive physical reservoir computing

Reference 17

Resolution: verified exact; doi, observed 2026-08-04T22:39:14.143166Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 2fad6147-01e5-4d8b-ab2a-94ab608deb2d · outbound

This paper cites Short- and long-term predictions of chaotic flows and extreme events: a physics-constrained reservoir computing approach.

IP-Basis PINNs: Efficient Multi-Query Inverse Parameter Estimation Short- and long-term predictions of chaotic flows and extreme events: a physics-constrained reservoir computing approach

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-08-04T22:39:14.372223Z

Source-reported events for the cited work

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Observation b629d586-97b5-48e1-97a0-ce220018ac1e · outbound

This paper cites Parameterized Physics-informed Neural Networks for Parameterized PDEs.

IP-Basis PINNs: Efficient Multi-Query Inverse Parameter Estimation Parameterized Physics-informed Neural Networks for Parameterized PDEs

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-04T22:39:13.577159Z

Source-reported events for the cited work

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Observation f8e3f114-49e3-44d5-9397-3aac5818a660 · outbound

This paper cites SVD-PINNs: Transfer Learning of Physics- Informed Neural Networks via Singular Value Decomposition.

IP-Basis PINNs: Efficient Multi-Query Inverse Parameter Estimation SVD-PINNs: Transfer Learning of Physics- Informed Neural Networks via Singular Value Decomposition

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:39:14.557126Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f84317d8-46b1-4da6-bc3f-3f175c7b2949 · outbound

This paper cites Transfer Learning in Physics-Informed Neural Networks: Full Fine-Tuning, Lightweight Fine-Tuning, and Low-Rank Adaptation.

IP-Basis PINNs: Efficient Multi-Query Inverse Parameter Estimation Transfer Learning in Physics-Informed Neural Networks: Full Fine-Tuning, Lightweight Fine-Tuning, and Low-Rank Adaptation

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-04T22:39:13.590127Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3c98f6d0-a6df-4f68-8df0-bd8323588d43 · outbound

This paper cites Physics-informed neural network with transfer learning (TL-PINN) based on domain similarity measure for prediction of nuclear reactor transients.

IP-Basis PINNs: Efficient Multi-Query Inverse Parameter Estimation Physics-informed neural network with transfer learning (TL-PINN) based on domain similarity measure for prediction of nuclear reactor transients

Reference 22

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Source-reported events for the cited work

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Observation ada8bb13-a9af-41e6-bef0-4977eb46b338 · outbound

This paper cites Transfer learning for deep neural network-based partial differential equations solv- ing.

IP-Basis PINNs: Efficient Multi-Query Inverse Parameter Estimation Transfer learning for deep neural network-based partial differential equations solv- ing

Reference 23

Resolution: malformed identifier; no resolver link, observed 2026-08-04T22:39:13.605452Z

Source-reported events for the cited work

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Observation 6eb021b6-c08c-4f1c-ba54-c111858af5d2 · outbound

This paper cites Scientific Machine Learning Through Physics–Informed Neural Networks: Where we are and What’s Next.

IP-Basis PINNs: Efficient Multi-Query Inverse Parameter Estimation Scientific Machine Learning Through Physics–Informed Neural Networks: Where we are and What’s Next

Reference 24

Resolution: verified exact; doi, observed 2026-08-04T22:39:14.061407Z

Source-reported events for the cited work

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Observation a74c5659-ec31-4bef-80d8-48cf96bc212e · outbound

This paper cites The Old and the New: Can Physics-Informed Deep-Learning Replace Traditional Linear Solvers?.

IP-Basis PINNs: Efficient Multi-Query Inverse Parameter Estimation The Old and the New: Can Physics-Informed Deep-Learning Replace Traditional Linear Solvers?

Reference 25

Resolution: metadata mismatch; local_arxiv, observed 2026-08-04T22:39:14.042685Z

Source-reported events for the cited work

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Observation 094f7b19-9572-4271-b3f7-f66fceb6ba78 · outbound

This paper cites A transfer learning-physics informed neural network (TL-PINN) for vortex- induced vibration.

IP-Basis PINNs: Efficient Multi-Query Inverse Parameter Estimation A transfer learning-physics informed neural network (TL-PINN) for vortex- induced vibration

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:39:14.536970Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c4200a17-1a4b-4587-94ce-ca9274e86278 · outbound

This paper cites On the Role of Fixed Points of Dynamical Systems in Training Physics-Informed Neural Networks.

IP-Basis PINNs: Efficient Multi-Query Inverse Parameter Estimation On the Role of Fixed Points of Dynamical Systems in Training Physics-Informed Neural Networks

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-04T22:39:13.634012Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 096b628a-68e6-4e05-b127-bb441f1b96fb · outbound

This paper cites How to Avoid Trivial Solutions in Physics-Informed Neural Networks.

IP-Basis PINNs: Efficient Multi-Query Inverse Parameter Estimation How to Avoid Trivial Solutions in Physics-Informed Neural Networks

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-04T22:39:13.640757Z

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Unavailable: canonical work link unavailable.

Observation 82e66959-5fcd-45c2-a2ce-b454cf0bdf16 · outbound

This paper cites dPotFit: A computer program to fit diatomic molecule spectral data to potential energy functions.

IP-Basis PINNs: Efficient Multi-Query Inverse Parameter Estimation dPotFit: A computer program to fit diatomic molecule spectral data to potential energy functions

Reference 29

Resolution: verified exact; doi, observed 2026-08-04T22:39:13.966777Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 12621419-0b35-4336-906d-7ccb0cde0d4e · outbound

This paper cites LEVEL: A computer program for solving the radial Schr¨ odinger equation for bound and quasibound levels.

IP-Basis PINNs: Efficient Multi-Query Inverse Parameter Estimation LEVEL: A computer program for solving the radial Schr¨ odinger equation for bound and quasibound levels

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:39:14.518240Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation df54b6cc-9f26-41a1-b25f-5c6f3053f99c · outbound

This paper cites Transfer learning based physics-informed neural networks for solving inverse problems in engineering structures under different loading scenarios.

IP-Basis PINNs: Efficient Multi-Query Inverse Parameter Estimation Transfer learning based physics-informed neural networks for solving inverse problems in engineering structures under different loading scenarios

Reference 31

Resolution: metadata mismatch; arxiv_id, observed 2026-08-04T22:39:14.337978Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation da6fe8ff-e704-4463-a862-a5d407bbafaf · outbound

This paper cites Transfer Learning-Based Coupling of Smoothed Finite Element Method and Physics-Informed Neural Network for Solving Elastoplastic Inverse Problems.

IP-Basis PINNs: Efficient Multi-Query Inverse Parameter Estimation Transfer Learning-Based Coupling of Smoothed Finite Element Method and Physics-Informed Neural Network for Solving Elastoplastic Inverse Problems

Reference 32

Resolution: verified exact; doi, observed 2026-08-04T22:39:13.944518Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8122cd3d-9562-40f1-a5dc-c119c05f7b58 · outbound

This paper cites A transfer learning physics-informed deep learning framework for modeling multiple solute dynamics in unsaturated soils.

IP-Basis PINNs: Efficient Multi-Query Inverse Parameter Estimation A transfer learning physics-informed deep learning framework for modeling multiple solute dynamics in unsaturated soils

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:39:14.497020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation afc86877-51cf-44b8-a523-0c0bcefd53e5 · outbound

This paper cites Gradient-enhanced physics-informed neural networks based on transfer learning for inverse problems of the variable coefficient differential equations.

IP-Basis PINNs: Efficient Multi-Query Inverse Parameter Estimation Gradient-enhanced physics-informed neural networks based on transfer learning for inverse problems of the variable coefficient differential equations

Reference 34

Resolution: verified exact; local_arxiv, observed 2026-08-04T22:39:13.923686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation cac5d88a-be1a-4457-8490-8774b1be1909 · outbound

This paper cites Physics-informed Neural Implicit Flow neural network for parametric PDEs.

IP-Basis PINNs: Efficient Multi-Query Inverse Parameter Estimation Physics-informed Neural Implicit Flow neural network for parametric PDEs

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:39:14.473310Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8ab2c9d8-4830-409e-9aea-4c9e64734f89 · outbound

This paper cites DeepXDE: A Deep Learning Library for Solving Differential Equations.

IP-Basis PINNs: Efficient Multi-Query Inverse Parameter Estimation DeepXDE: A Deep Learning Library for Solving Differential Equations

Reference 36

Resolution: verified exact; doi, observed 2026-08-04T22:39:13.885452Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 3d0bb52a-9dcb-4cce-b7be-462c93727a73 · outbound

This paper cites Enhancing Symbolic Regression and Universal Physics-Informed Neural Networks with Dimensional Analysis.

IP-Basis PINNs: Efficient Multi-Query Inverse Parameter Estimation Enhancing Symbolic Regression and Universal Physics-Informed Neural Networks with Dimensional Analysis

Reference 37

Resolution: verified exact; local_arxiv, observed 2026-08-04T22:39:13.858338Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 59bd8d75-b822-4f2b-8c4a-7d4950c30fc4 · outbound

This paper cites A transfer learning enhanced physics-informed neural network for parameter identification in soft materials.

IP-Basis PINNs: Efficient Multi-Query Inverse Parameter Estimation A transfer learning enhanced physics-informed neural network for parameter identification in soft materials

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:39:14.449618Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 206d62e1-018e-4b34-9ddd-d966297c229f · outbound

This paper cites Lazy multivariate higher-order forward-mode AD.

IP-Basis PINNs: Efficient Multi-Query Inverse Parameter Estimation Lazy multivariate higher-order forward-mode AD

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-04T22:39:13.732110Z

Source-reported events for the cited work

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Observation 9e47df3a-53e6-4840-8d57-0eac5349b941 · outbound

This paper cites an unresolved cited work.

IP-Basis PINNs: Efficient Multi-Query Inverse Parameter Estimation Unresolved cited work

Reference 40

Resolution: unresolved; raw_fallback, observed 2026-08-04T22:39:14.430477Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 48c20101-0a23-4b58-9a20-b32fc8999e40 · outbound

This paper cites One-Shot Transfer Learning for Nonlinear ODEs.

IP-Basis PINNs: Efficient Multi-Query Inverse Parameter Estimation One-Shot Transfer Learning for Nonlinear ODEs

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-04T22:39:13.745212Z

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Unavailable: canonical work link unavailable.

Pith citing papers

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