Paper Citation Record · LEDGER

Physics-informed reduced order model with conditional neural fields

As of 23 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 1 inbound Pith citation observation for arXiv:2412.05233.

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

pith.paper-citation-record.v1
2412.05233 v1

Coverage vector

measured 26 of 26 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T20:53:44.449029Z

measured 27 of 27 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-27T22:47:53.545294Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T16:27:08.483493Z

Reference resolution

26 of 26 outbound references displayed

verified exact0
verified fuzzy15
unresolved11
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation cacd2888-cbef-49af-97b0-a00896510eed · outbound

This paper cites The gnat method for nonlinear model reduction: Effective implementation and application to computational fluid dynamics and turbulent flows.

Physics-informed reduced order model with conditional neural fields The gnat method for nonlinear model reduction: Effective implementation and application to computational fluid dynamics and turbulent flows

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:53:45.125206Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 9d76c9ac-319d-4973-b085-4e739d1cbcf2 · outbound

This paper cites Efficient space–time reduced order model for linear dynamical systems in python using less than 120 lines of code.

Physics-informed reduced order model with conditional neural fields Efficient space–time reduced order model for linear dynamical systems in python using less than 120 lines of code

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:53:45.101565Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 5f63bb51-c164-47d9-87df-ebdd5bd863e4 · outbound

This paper cites Reduced order models for lagrangian hydrodynamics.

Physics-informed reduced order model with conditional neural fields Reduced order models for lagrangian hydrodynamics

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-11T20:53:44.304504Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5d6ac9c5-6a49-4af4-b8c4-5f4398afc7f1 · outbound

This paper cites Space–time least-squares petrov–galerkin projection for nonlinear model reduction.

Physics-informed reduced order model with conditional neural fields Space–time least-squares petrov–galerkin projection for nonlinear model reduction

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-11T20:53:44.310349Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8f962772-d486-415d-b5f1-13ef28c8b515 · outbound

This paper cites SNS: A solution-based nonlinear subspace method for time-dependent model order reduction.

Physics-informed reduced order model with conditional neural fields SNS: A solution-based nonlinear subspace method for time-dependent model order reduction

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:53:45.030310Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation ea71ad6c-1110-48a8-9dd5-bc012fa091d0 · outbound

This paper cites Latent-space dynamics for reduced deformable simulation.

Physics-informed reduced order model with conditional neural fields Latent-space dynamics for reduced deformable simulation

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:53:45.000200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 20cbee75-dc8e-4639-906c-9e9449c820b5 · outbound

This paper cites Carlberg.

Physics-informed reduced order model with conditional neural fields Carlberg

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:53:44.978009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 1c652a36-0c0c-43d5-89ca-a07e130e390b · outbound

This paper cites A fast and accurate physics-informed neural network reduced order model with shallow masked autoencoder.

Physics-informed reduced order model with conditional neural fields A fast and accurate physics-informed neural network reduced order model with shallow masked autoencoder

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-11T20:53:44.338221Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ffb515a8-5b6a-4c01-b9cb-bcd90e7de5d8 · outbound

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

Physics-informed reduced order model with conditional neural fields Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-11T20:53:44.343163Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f4bccd6b-c09a-4d6d-91e3-1780f41f81aa · outbound

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

Physics-informed reduced order model with conditional neural fields Physics-informed neural networks (PINNs) for fluid mechanics: A review

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-11T20:53:44.349099Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5015ec70-bdf1-4a03-b11d-cbe35b101adf · outbound

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

Physics-informed reduced order model with conditional neural fields Parameterized Physics-informed Neural Networks for Parameterized PDEs

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-11T20:53:44.354586Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4a44aa5e-3c62-4acd-a350-54a31a1b590a · outbound

This paper cites Implicit neural representations with periodic activation functions.

Physics-informed reduced order model with conditional neural fields Implicit neural representations with periodic activation functions

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-11T20:53:44.361707Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0d4fe754-c004-4169-bb7d-3d687173d9aa · outbound

This paper cites Fourier features let networks learn high frequency functions in low dimensional domains.

Physics-informed reduced order model with conditional neural fields Fourier features let networks learn high frequency functions in low dimensional domains

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-11T20:53:44.368700Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation be706f00-2475-479c-a7ea-70a1c0fc1866 · outbound

This paper cites Continuous PDE dynamics forecasting with implicit neural representations.

Physics-informed reduced order model with conditional neural fields Continuous PDE dynamics forecasting with implicit neural representations

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:53:44.848860Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d55b8623-4a51-4501-b515-4b015cc88c67 · outbound

This paper cites Crom: Continuous reduced-order modeling of pdes using implicit neural representations.

Physics-informed reduced order model with conditional neural fields Crom: Continuous reduced-order modeling of pdes using implicit neural representations

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:53:44.822594Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 6c957073-3af9-4051-9aef-08f0b2edf2d4 · outbound

This paper cites Evolve smoothly, fit consis- tently: Learning smooth latent dynamics for advection-dominated systems.

Physics-informed reduced order model with conditional neural fields Evolve smoothly, fit consis- tently: Learning smooth latent dynamics for advection-dominated systems

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:53:44.797765Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation e371e517-9bb5-4510-96cb-f9ae0ece55e1 · outbound

This paper cites an unresolved cited work.

Physics-informed reduced order model with conditional neural fields Unresolved cited work

Reference 17

Resolution: unresolved; raw_fallback, observed 2026-08-11T20:53:44.769377Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 34c621a4-ded7-4d37-ba9d-8903ab4b33c3 · outbound

This paper cites Reduced-order modeling for parameterized pdes via implicit neural representations.

Physics-informed reduced order model with conditional neural fields Reduced-order modeling for parameterized pdes via implicit neural representations

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:53:44.744511Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation ea0bab4b-fb0c-4885-af52-9d69f9fb041e · outbound

This paper cites Sukumar and Ankit Srivastava.

Physics-informed reduced order model with conditional neural fields Sukumar and Ankit Srivastava

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:53:44.720752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 60964be7-a238-49a5-b37d-822ebd24490f · outbound

This paper cites Gladstone, Mohammad A.

Physics-informed reduced order model with conditional neural fields Gladstone, Mohammad A

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:53:44.693455Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 4ee22751-7be6-4f06-b050-9895a7dae51f · outbound

This paper cites Neural fields in visual computing and beyond.

Physics-informed reduced order model with conditional neural fields Neural fields in visual computing and beyond

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-11T20:53:44.420386Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5bbbc970-46e8-40f3-bca6-21494ff48a0f · outbound

This paper cites Vectorized conditional neural fields: A framework for solving time-dependent parametric partial differential equations.

Physics-informed reduced order model with conditional neural fields Vectorized conditional neural fields: A framework for solving time-dependent parametric partial differential equations

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:53:44.642056Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 46d30e8e-a877-4256-8b4a-ec460fb54b27 · outbound

This paper cites Multiplicative filter networks.

Physics-informed reduced order model with conditional neural fields Multiplicative filter networks

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:53:44.617497Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 572e594e-8900-4514-86b3-d2f82ef580c6 · outbound

This paper cites Chen, Yulia Rubanova, Jesse Bettencourt, and David K Duvenaud.

Physics-informed reduced order model with conditional neural fields Chen, Yulia Rubanova, Jesse Bettencourt, and David K Duvenaud

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:53:44.592690Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 32430e74-c841-451e-984a-befe18eda934 · outbound

This paper cites an unresolved cited work.

Physics-informed reduced order model with conditional neural fields Unresolved cited work

Reference 25

Resolution: unresolved; raw_fallback, observed 2026-08-11T20:53:44.570595Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 28abb4c6-ec65-4360-bafc-68ec0fd32e91 · outbound

This paper cites Deepsdf: Learning continuous signed distance functions for shape representation.

Physics-informed reduced order model with conditional neural fields Deepsdf: Learning continuous signed distance functions for shape representation

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:53:44.543842Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Pith citing papers

Observation 56001cec-5e90-4942-9aba-f642019fb1c8 · inbound

Architecture Shapes Transfer Specificity in Implicit Neural Representations cites this paper.

Architecture Shapes Transfer Specificity in Implicit Neural Representations Physics-informed reduced order model with conditional neural fields

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-07-02T16:27:08.485151Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.