Paper Citation Record · LEDGER

DeepXDE: A deep learning library for solving differential equations

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 14 inbound Pith citation observations for arXiv:1907.04502.

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

pith.paper-citation-record.v1
1907.04502 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 14 of 14 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:15:20.758082Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-08T16:55:08.403158Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
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malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation e9421cde-6f1e-45ac-aa31-75a21c8a13a5 · inbound

DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators cites this paper.

DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators DeepXDE: A deep learning library for solving differential equations

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-15T03:17:25.374340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 534229ca-0367-4424-9598-3f3be24bf974 · inbound

Universal Differential Equations for Scientific Machine Learning cites this paper.

Universal Differential Equations for Scientific Machine Learning DeepXDE: A deep learning library for solving differential equations

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-05-18T00:24:43.345114Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 02cb394a-6ef7-4c7e-941d-66f73b0928c6 · inbound

Deep learning applied to computational mechanics: A comprehensive review, state of the art, and the classics cites this paper.

Deep learning applied to computational mechanics: A comprehensive review, state of the art, and the classics DeepXDE: A deep learning library for solving differential equations

Reference 273

Resolution: verified exact; arxiv_id, observed 2026-05-24T10:24:20.273209Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 87f91273-f837-45ea-a5f0-0e2498943f86 · inbound

Partial-differential-algebraic equations of nonlinear dynamics by Physics-Informed Neural-Network: (I) Operator splitting and framework assessment cites this paper.

Partial-differential-algebraic equations of nonlinear dynamics by Physics-Informed Neural-Network: (I) Operator splitting and framework assessment DeepXDE: A deep learning library for solving differential equations

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-23T22:58:34.401658Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 0e7fee0b-779f-4e1b-a395-86aa6f30dbf2 · inbound

Geometry-aware PINNs for Turbulent Flow Prediction cites this paper.

Geometry-aware PINNs for Turbulent Flow Prediction DeepXDE: A deep learning library for solving differential equations

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-12T00:08:09.232971Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2c482d4f-ae67-4760-8b10-72f26c8c91b3 · inbound

Convergence of Physics-Informed Neural Networks for Fully Nonlinear PDE's cites this paper.

Convergence of Physics-Informed Neural Networks for Fully Nonlinear PDE's DeepXDE: A deep learning library for solving differential equations

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-11T12:07:19.200561Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 32ee540e-76f4-4da0-a13e-126bcbd686a4 · inbound

How Learnable Grids Recover Fine Detail in Low Dimensions: A Neural Tangent Kernel Analysis of Multigrid Parametric Encodings cites this paper.

How Learnable Grids Recover Fine Detail in Low Dimensions: A Neural Tangent Kernel Analysis of Multigrid Parametric Encodings DeepXDE: A deep learning library for solving differential equations

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-16T12:15:20.758082Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8fbb337a-ff2b-4a14-912a-56c4620da4a5 · inbound

Hybrid Adaptive Modeling in Process Monitoring: Leveraging Sequence Encoders and Physics-Informed Neural Networks cites this paper.

Hybrid Adaptive Modeling in Process Monitoring: Leveraging Sequence Encoders and Physics-Informed Neural Networks DeepXDE: A deep learning library for solving differential equations

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T15:42:50.458811Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 85323955-890a-4ba8-bdbd-aa249540f355 · inbound

Estimation of Hemodynamic Parameters via Physics Informed Neural Networks including Hematocrit Dependent Rheology cites this paper.

Estimation of Hemodynamic Parameters via Physics Informed Neural Networks including Hematocrit Dependent Rheology DeepXDE: A deep learning library for solving differential equations

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-06T04:35:57.299669Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a84da6cc-ccab-4684-a24d-d329cf2d5500 · inbound

Extending deep learning U-Net architecture for predicting unsteady fluid flows in textured microchannels cites this paper.

Extending deep learning U-Net architecture for predicting unsteady fluid flows in textured microchannels DeepXDE: A deep learning library for solving differential equations

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-13T18:38:07.633143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation a5aef369-85af-4baa-97c2-7a1663d0420e · inbound

Physics-Informed Neural Networks for Solving Two-Flavor Neutrino Oscillations in Vacuum and Matter Environments for Atmospheric and Reactor Neutrinos cites this paper.

Physics-Informed Neural Networks for Solving Two-Flavor Neutrino Oscillations in Vacuum and Matter Environments for Atmospheric and Reactor Neutrinos DeepXDE: A deep learning library for solving differential equations

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-05-11T14:16:20.093122Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 18dda1c8-87bd-4373-9366-8ba869286fd9 · inbound

Physics-Informed Neural Networks for Solving Two-Flavor Neutrino Oscillations in Vacuum and Matter Environments for Atmospheric and Reactor Neutrinos cites this paper.

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-05-14T22:18:04.128463Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 6076bf3e-0b69-427d-8f71-070f8eed8dd0 · inbound

Frequency-Domain Neural ODEs for Modeling Non-Linear Dynamical Systems cites this paper.

Frequency-Domain Neural ODEs for Modeling Non-Linear Dynamical Systems DeepXDE: A deep learning library for solving differential equations

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-07-04T07:59:39.702374Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation dca11367-663e-41ae-b512-9e6ca3ac5130 · inbound

Mass-Conserving Physics-Informed Neural Networks For The One-Dimensional Advection-Diffusion Equation cites this paper.

Mass-Conserving Physics-Informed Neural Networks For The One-Dimensional Advection-Diffusion Equation DeepXDE: A deep learning library for solving differential equations

Reference 29

Resolution: verified exact; local_arxiv, observed 2026-07-08T16:55:08.404689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.