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Paper Citation Record · LEDGER

jinns: a JAX Library for Physics-Informed Neural Networks

As of 16 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 0 inbound Pith citation observations for arXiv:2412.14132.

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

pith.paper-citation-record.v1
2412.14132 v1

Coverage vector

measured 17 of 17 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T12:29:34.686969Z

measured 17 of 17 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

17 of 17 outbound references displayed

  • verified exact1
  • verified fuzzy10
  • unresolved6
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9e17b57c-a0c0-411c-b172-f10d492f6d1d · outbound

This paper cites Araz, Juan Carlos Criado, and Michael Spannwosky.

jinns: a JAX Library for Physics-Informed Neural Networks Araz, Juan Carlos Criado, and Michael Spannwosky

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:29:35.315000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-11T12:29:34.445267Z digest=sha256:926eec11a384862ba1fb7a39aee167dc7873b4dda1ce02f86410a286bf87a7b4

Observation 711cc893-390d-476d-960c-1baad59e6635 · outbound

This paper cites JAX : composable transformations of P ython+ N um P y programs, 2024.

jinns: a JAX Library for Physics-Informed Neural Networks JAX : composable transformations of P ython+ N um P y programs, 2024

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:29:35.275229Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-11T12:29:34.457105Z digest=sha256:5a0335c8a731b0c7e95935d4c368105fd98ce91364d7c7aace47da61d5a01f7d

Observation 80cdaec1-a2df-4f46-a5a7-c975c149e3bb · outbound

This paper cites Separable physics-informed neural networks.

jinns: a JAX Library for Physics-Informed Neural Networks Separable physics-informed neural networks

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:29:35.231541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-11T12:29:34.471343Z digest=sha256:9ccf2d0407cfb18ef3b36b930f05835a9435bf61ab40784f33865ff2c30638ec

Observation 0e9cf46d-aa9f-4aa5-b699-2c745116d8f3 · outbound

This paper cites Physics-informed neural networks for advanced modeling.

jinns: a JAX Library for Physics-Informed Neural Networks Physics-informed neural networks for advanced modeling

Reference 4

Resolution
verified exact
doi, observed 2026-08-11T12:29:34.782320Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-11T12:29:34.480490Z digest=sha256:159ef93a8c29a395201f34d6b95d87dc7669f74aab330a3d0ddc1a5e196b1f37

Observation a33f8ec8-497b-4f88-9dc2-63dd6117b865 · outbound

This paper cites Scientific machine learning through physics--informed neural networks: Where we are and what’s next.

jinns: a JAX Library for Physics-Informed Neural Networks Scientific machine learning through physics--informed neural networks: Where we are and what’s next

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:29:35.195453Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-11T12:29:34.500824Z digest=sha256:40183b735327143393c0e90a7f13cc5b9ba80091cf6a43294fa59c745f893e09

Observation db17b71d-6644-4eee-8465-86da45089a36 · outbound

This paper cites Systems biology: Identifiability analysis and parameter identification via systems-biology-informed neural networks.

jinns: a JAX Library for Physics-Informed Neural Networks Systems biology: Identifiability analysis and parameter identification via systems-biology-informed neural networks

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:29:35.161787Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-11T12:29:34.507065Z digest=sha256:23869319e657b1c1ba8db7b9419b7b2c7afff7c4a66bd225b16ebe805629d2dc

Observation 727303ac-b875-47df-8b42-e19c901c1b59 · outbound

This paper cites Hyperpinn: Learning parameterized differential equations with physics-informed hypernetworks.

jinns: a JAX Library for Physics-Informed Neural Networks Hyperpinn: Learning parameterized differential equations with physics-informed hypernetworks

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:29:35.121766Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-11T12:29:34.518150Z digest=sha256:9be67b700fd044fc7118cb47348aca0bcc4847fdaa48bfcc99081cd2b3457d4f

Observation ab36142b-d56f-4140-83cd-cc222e6f07c9 · outbound

This paper cites PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs.

jinns: a JAX Library for Physics-Informed Neural Networks PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-11T12:29:34.537720Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:29:34.537720Z digest=sha256:619ad0e77d236e7646a423880e68ed592abc92f3a40525501ae6c6470e8a6432

Observation e28a9427-3cce-4fd4-9ac0-28e363d1df81 · outbound

This paper cites Physics-informed machine learning.

jinns: a JAX Library for Physics-Informed Neural Networks Physics-informed machine learning

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-11T12:29:34.559410Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:29:34.559410Z digest=sha256:cf25038a489fc4678b98dfc8c68cc583c2bf0bfdc7a668c0301f6944a6e33e47

Observation aed13a26-bcd4-4d12-a4c3-f9fc79887b5c · outbound

This paper cites Fourier Neural Operator for Parametric Partial Differential Equations.

jinns: a JAX Library for Physics-Informed Neural Networks Fourier Neural Operator for Parametric Partial Differential Equations

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-11T12:29:34.567067Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:29:34.567067Z digest=sha256:30d507dda2ec59ab29646a7b6d039fb738348e03027af869075b1104f5b661e4

Observation 3c21fb90-6c67-45dd-943a-8f87a025f0cc · outbound

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

jinns: a JAX Library for Physics-Informed Neural Networks DeepXDE : A deep learning library for solving differential equations

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-11T12:29:34.577847Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:29:34.577847Z digest=sha256:22dbf6e43e7dcdd378059d47c861df05bd48295b06be70d1190e47bc5e2bd7ca

Observation 6622845c-15cc-4eb6-bea4-4bfad56d463a · outbound

This paper cites Nvidia modulus, 2023.

jinns: a JAX Library for Physics-Informed Neural Networks Nvidia modulus, 2023

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:29:35.031113Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-11T12:29:34.592826Z digest=sha256:35f8174d13c535a3f3d48a6fc1cb22507a673ff5944d3a1981584b90eed8d277

Observation 868b46ed-bc59-4719-83f9-31b2de670b07 · outbound

This paper cites Idrlnet: A physics-informed neural network library.

jinns: a JAX Library for Physics-Informed Neural Networks Idrlnet: A physics-informed neural network library

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:29:34.994278Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-11T12:29:34.628892Z digest=sha256:2c640384bd39ea47e070cd6989794089e1cec72dbd1479763f391e21559a18f6

Observation 3b5b7bd9-04d6-4882-bcad-bf82d6e8b878 · outbound

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

jinns: a JAX Library for Physics-Informed Neural Networks Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-11T12:29:34.640164Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:29:34.640164Z digest=sha256:a0a8c23a3232c6fe11844fe823f6d57a68e8f9793005d79a22b00dd40e5ef3ff

Observation 99f0fe0c-afa7-402b-b97a-689fcc3efdd1 · outbound

This paper cites Spatio-temporal ecological models via physics-informed neural networks for studying chronic wasting disease.

jinns: a JAX Library for Physics-Informed Neural Networks Spatio-temporal ecological models via physics-informed neural networks for studying chronic wasting disease

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:29:34.920595Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-11T12:29:34.656478Z digest=sha256:50889df52e1dce7d04cb3260f7accd834dbbeeeaec03b7d08bdcc6dc4901a5c7

Observation 6ac42f95-607d-49e8-b60c-d8744d3bad99 · outbound

This paper cites Pdebench: An extensive benchmark for scientific machine learning.

jinns: a JAX Library for Physics-Informed Neural Networks Pdebench: An extensive benchmark for scientific machine learning

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:29:34.899770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-11T12:29:34.667868Z digest=sha256:a50c91217e7ce80c352e15ebe9e887040a3db23e8743a8b468d7560b53225902

Observation dac723bf-275a-4ed0-b115-64ba2f3c389c · outbound

This paper cites NeuralPDE: Automating Physics-Informed Neural Networks (PINNs) with Error Approximations.

jinns: a JAX Library for Physics-Informed Neural Networks NeuralPDE: Automating Physics-Informed Neural Networks (PINNs) with Error Approximations

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-11T12:29:34.686969Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:29:34.686969Z digest=sha256:4c6c421fc53b64558543279b7766ebbae40fbf26c2cdaec0a474fb540b126f03

Pith citing papers

No inbound Pith citation observations are available.