Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-05-08T06:43:07.836039Z
Paper Citation Record · LEDGER
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions
As of 21 July 2026, this Paper Citation Record lists 72 of 72 outbound references and 3 inbound Pith citation observations for arXiv:2604.23528.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-07-21T06:31:05.380196+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-07-13T06:59:52.656435Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-07-02T11:36:55.277146Z
Reference resolution
72 of 72 outbound references displayed
- verified exact13
- verified fuzzy55
- unresolved0
- parse uncertain0
- malformed identifier1
- metadata mismatch3
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 162f3dda-4302-4e1e-90ae-695ab6fd323c · outbound
This paper cites an unresolved cited work.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Unresolved cited work
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T18:32:51.910846Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation 7b5ff37f-36ee-4422-aba7-2add1dc87849 · outbound
This paper cites Physics- informed machine learning.Nature Reviews Physics, pages 1–19.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Physics- informed machine learning.Nature Reviews Physics, pages 1–19
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T18:32:51.771132Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation 997eaed9-30c8-403f-b612-e64c13bfa017 · outbound
This paper cites Simulating t hree-dimensional turbulence with physics-informed neural networks.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Simulating t hree-dimensional turbulence with physics-informed neural networks
Reference 3
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T21:06:14.613959Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation cf89a39c-12fa-467b-ac05-0d0b143966a1 · outbound
This paper cites A physics-informed deep learning framework for inversion and surrogate modeling in solid mechanics.Computer Methods in Applied Mechanics and Engineering, 379:113741.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions A physics-informed deep learning framework for inversion and surrogate modeling in solid mechanics.Computer Methods in Applied Mechanics and Engineering, 379:113741
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T18:32:51.939702Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation b38b5c09-df80-45aa-84c7-bdbc2e013052 · outbound
This paper cites Physics-informed neural networks for inverse problems in nano-optics and metamaterials.Optics express, 28(8):11618–11633.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Physics-informed neural networks for inverse problems in nano-optics and metamaterials.Optics express, 28(8):11618–11633
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T18:32:51.889826Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation a4de0e9c-2ef6-4017-9e9d-6e7a43ab4cd4 · outbound
This paper cites Physics-informed neural networks for multiphysics data assimilation with application to subsurface transport.Advances in Water Resources, 141:103610.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Physics-informed neural networks for multiphysics data assimilation with application to subsurface transport.Advances in Water Resources, 141:103610
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T18:32:51.810804Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation 5d63093f-f4a8-4fc6-b96e-438547a62b49 · outbound
This paper cites B-pinns: Bayesian physics-informed neural networks for forward and inverse pde problems with noisy data.Journal of Computational Physics, 425:109913.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions B-pinns: Bayesian physics-informed neural networks for forward and inverse pde problems with noisy data.Journal of Computational Physics, 425:109913
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T18:32:51.841949Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation 225df47f-27e0-4dd2-b091-4a148446483d · outbound
This paper cites Bayesian physics informed neural networks for real-world nonlinear dynamical systems.Computer Methods in Applied Mechanics and Engineering, 402:115346.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Bayesian physics informed neural networks for real-world nonlinear dynamical systems.Computer Methods in Applied Mechanics and Engineering, 402:115346
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T18:32:51.914397Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation 51afa77c-6e95-4c18-84ef-a2de575fe8f8 · outbound
This paper cites Deep hidden physics models: Deep learning of nonlinear partial differential equations.The Journal of Machine Learning Research, 19(1):932–955.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Deep hidden physics models: Deep learning of nonlinear partial differential equations.The Journal of Machine Learning Research, 19(1):932–955
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T18:32:51.778921Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation e9424fc6-38e7-49b8-a772-53ccd8676d44 · outbound
This paper cites Hidden fluid mechanics: Learning velocity and pressure fields from flow visualizations.Science, 367(6481):1026–1030.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Hidden fluid mechanics: Learning velocity and pressure fields from flow visualizations.Science, 367(6481):1026–1030
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T18:32:51.936174Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation 7a07913d-8c3a-4e6c-b221-614fe002595f · outbound
This paper cites Deep learning the flow law of antarctic ice shelves.Science, 387(6739):1219–1224.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Deep learning the flow law of antarctic ice shelves.Science, 387(6739):1219–1224
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T18:32:51.900038Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation 5df1311c-ac9c-4e06-a9cd-0c1ce7f63c35 · outbound
This paper cites Physics-informed deep learning for incompressible laminar flows.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Physics-informed deep learning for incompressible laminar flows
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T18:32:51.918153Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation 6e877ff7-e15c-4bdd-b632-807c2ade2ea6 · outbound
This paper cites Physics-informed neural networks for heat transfer problems.Journal of Heat Transfer, 143(6).
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Physics-informed neural networks for heat transfer problems.Journal of Heat Transfer, 143(6)
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T18:32:51.921676Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation 0fe61e0c-824f-4b5e-be81-197f8a59aa07 · outbound
This paper cites Analyses of internal structures and defects in materials using physics-informed neural networks.Science advances, 8(7):eabk0644.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Analyses of internal structures and defects in materials using physics-informed neural networks.Science advances, 8(7):eabk0644
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T18:32:51.903497Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation 0cd2f370-ef5e-44a4-9c7b-a662c9525e08 · outbound
This paper cites an unresolved cited work.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Unresolved cited work
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T18:32:51.950543Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation a08f75ba-87df-495c-ae7a-e383af519cbe · outbound
This paper cites Physics-informed neural networks for studying heat transfer in porous media.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Physics-informed neural networks for studying heat transfer in porous media
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T18:32:51.907255Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation bf5a1abe-2d82-448b-b936-33ddc6526635 · outbound
This paper cites an unresolved cited work.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Unresolved cited work
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T18:32:51.875041Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation 7ce558b9-d27d-4295-8b64-d664b0e9988f · outbound
This paper cites Physics- informed neural networks for a lithium-ion batteries model: A case of study.Advances in Computational Science & Engineering (ACSE), 2(4).
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Physics- informed neural networks for a lithium-ion batteries model: A case of study.Advances in Computational Science & Engineering (ACSE), 2(4)
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T18:32:51.947269Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation f291eac1-0563-4dbc-be5b-c0f29632d83c · outbound
This paper cites Physics informed neural networks reveal valid models for reactive diffusion of volatiles through paper.Chemical Engineering Science, 285:119636.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Physics informed neural networks reveal valid models for reactive diffusion of volatiles through paper.Chemical Engineering Science, 285:119636
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T18:32:51.762647Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation 2207b3b1-0f22-4cb9-93de-06370400c4e0 · outbound
This paper cites Physics-informed neural networks for transcranial ultrasound wave propagation.Ultrasonics, 132:107026.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Physics-informed neural networks for transcranial ultrasound wave propagation.Ultrasonics, 132:107026
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T18:32:51.819688Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation 022d5536-4095-4391-bd02-9010a1c32434 · outbound
This paper cites Physics-informed deep neural networks for learning parameters and constitutive relationships in subsurface flow problems.Water Resources Research, 56(5):e2019WR026731.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Physics-informed deep neural networks for learning parameters and constitutive relationships in subsurface flow problems.Water Resources Research, 56(5):e2019WR026731
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T18:32:51.827222Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation f82ac1e4-00d3-4ece-8707-07fcdab52f26 · outbound
This paper cites Physics informed deep learning for flow and transport in porous media.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Physics informed deep learning for flow and transport in porous media
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T18:32:51.802725Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation a9ddb9d8-1a69-4c48-9963-fcc7258a86e7 · outbound
This paper cites an unresolved cited work.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Unresolved cited work
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T18:32:51.924952Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation 0a642890-20ab-43de-ad7f-80a2be924ef9 · outbound
This paper cites an unresolved cited work.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Unresolved cited work
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T18:32:51.774943Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation 978b4e59-39a3-4d6f-b688-298e4f00994d · outbound
This paper cites Physics-informed neural networks for modeling physiological time series for cuffless blood pressure estimation.npj Digital Medicine, 6(1):110.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Physics-informed neural networks for modeling physiological time series for cuffless blood pressure estimation.npj Digital Medicine, 6(1):110
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T18:32:51.858920Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation 917820c4-0d1d-45f4-8cf1-e05fc2f47a0f · outbound
This paper cites an unresolved cited work.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Unresolved cited work
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T18:32:51.782272Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation d6f4b61e-64cf-46bb-a1d9-49b0c52e1fae · outbound
This paper cites an unresolved cited work.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Unresolved cited work
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T18:32:51.878447Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation 796a2413-c57a-49ed-b15a-61bb525010e1 · outbound
This paper cites Piratenets: Physics-informed deep learning with residual adaptive networks.Journal of Machine Learning Research, 25(402):1–51.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Piratenets: Physics-informed deep learning with residual adaptive networks.Journal of Machine Learning Research, 25(402):1–51
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T18:32:51.943568Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation cf38194b-34db-4c20-b466-388768447ec0 · outbound
This paper cites Finite Basis Physics-Informed Neural Networks (FBPINNs): a scalable domain decomposition approach for solving differential equations.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Finite Basis Physics-Informed Neural Networks (FBPINNs): a scalable domain decomposition approach for solving differential equations
Reference 29
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T21:06:14.695237Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation c6c4940b-df26-4ac1-83b9-3b06637ff493 · outbound
This paper cites PINNsFormer: A Transformer-Based Framework For Physics-Informed Neural Networks.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions PINNsFormer: A Transformer-Based Framework For Physics-Informed Neural Networks
Reference 30
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-11T21:06:14.680626Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation 99b6223e-3cd1-463c-b9d6-824ee6c994eb · outbound
This paper cites Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism
Reference 31
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-11T21:06:14.661201Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation 84c93060-981a-444c-93c2-ec25ff34170d · outbound
This paper cites When and why PINNs fail to train: A neural tangent kernel perspective.Journal of Computational Physics, 449:110768.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions When and why PINNs fail to train: A neural tangent kernel perspective.Journal of Computational Physics, 449:110768
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T18:32:51.758457Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation ee548c45-15b0-4eca-bf3d-9cc170e45bd1 · outbound
This paper cites Multi-objective loss balancing for physics-informed deep learning.Computer Methods in Applied Mechanics and Engineering, 439:117914.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Multi-objective loss balancing for physics-informed deep learning.Computer Methods in Applied Mechanics and Engineering, 439:117914
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T18:32:51.850385Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation e5ac1cd6-07bb-4336-a53c-edd4b3761b81 · outbound
This paper cites Challenges in Training PINNs: A Loss Landscape Perspective.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Challenges in Training PINNs: A Loss Landscape Perspective
Reference 34
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T21:06:14.690098Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation 18287929-970a-4277-89f9-ef81f3e9f6e0 · outbound
This paper cites Achieving high accuracy with pinns via energy natural gradient descent.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Achieving high accuracy with pinns via energy natural gradient descent
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T18:32:51.845968Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation d8c59a01-69b3-48f4-b741-603ed62cb07b · outbound
This paper cites Gradient alignment in physics-informed neural networks: A second-order optimization perspective.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Gradient alignment in physics-informed neural networks: A second-order optimization perspective
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T18:32:51.882210Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation 84e84f52-2b3c-4156-a918-b74e6c424b5f · outbound
This paper cites an unresolved cited work.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Unresolved cited work
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T18:32:51.749418Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation 9756a0cd-19b2-4af1-ae28-150d4efcfc8b · outbound
This paper cites Failure-informed adaptive sampling for pinns.SIAM Journal on Scientific Computing, 45(4):A1971–A1994.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Failure-informed adaptive sampling for pinns.SIAM Journal on Scientific Computing, 45(4):A1971–A1994
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T18:32:51.893259Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation 250d4935-80df-48ad-b2b0-809b64aa27f9 · outbound
This paper cites an unresolved cited work.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Unresolved cited work
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T18:32:51.806205Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation 41b24e85-8a10-4533-a7ae-7df4188cc441 · outbound
This paper cites Mitigating Propagation Failures in Physics-informed Neural Networks using Retain-Resample-Release (R3) Sampling.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Mitigating Propagation Failures in Physics-informed Neural Networks using Retain-Resample-Release (R3) Sampling
Reference 40
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T21:06:14.674624Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation a868345f-6d25-413c-ba41-be848a2c9892 · outbound
This paper cites an unresolved cited work.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Unresolved cited work
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T18:32:51.896769Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation 2a718ccd-13b2-4e36-af28-91359aa5fa68 · outbound
This paper cites Physics-informed neural networks for high-frequency and multi-scale problems using transfer learning.Applied Sciences, 14(8):3204.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Physics-informed neural networks for high-frequency and multi-scale problems using transfer learning.Applied Sciences, 14(8):3204
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T18:32:51.786536Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation 19e623dc-22f0-43c1-aa8f-6435cef72a05 · outbound
This paper cites Understanding and mitigating gradient flow pathologies in physics-informed neural networks.SIAM Journal on Scientific Computing, 43(5):A3055–A3081.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Understanding and mitigating gradient flow pathologies in physics-informed neural networks.SIAM Journal on Scientific Computing, 43(5):A3055–A3081
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T18:32:51.766849Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation f5db0f2d-a507-4782-a6b0-51c6221ebe70 · outbound
This paper cites Residual- based attention in physics-informed neural networks.Computer Methods in Applied Mechanics and Engineering, 421:116805.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Residual- based attention in physics-informed neural networks.Computer Methods in Applied Mechanics and Engineering, 421:116805
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T18:32:51.798838Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation dce9aed1-c445-49eb-8632-962f0e31f43b · outbound
This paper cites ConFIG: Towards Conflict-free Training of Physics Informed Neural Networks.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions ConFIG: Towards Conflict-free Training of Physics Informed Neural Networks
Reference 45
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T21:06:14.583409Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation 7ba2277a-8801-4341-914c-4e697008f803 · outbound
This paper cites Characterizing possible failure modes in physics-informed neural networks.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Characterizing possible failure modes in physics-informed neural networks
Reference 46
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T21:06:14.599714Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation 4eacd0fd-7958-4f86-8e97-2f3bea9c7088 · outbound
This paper cites an unresolved cited work.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Unresolved cited work
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T18:32:51.794068Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation 8d7b8e97-8878-4061-af40-624fd98834e4 · outbound
This paper cites Respecting causality for training physics-informed neural networks.Computer Methods in Applied Mechanics and Engineering, 421:116813.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Respecting causality for training physics-informed neural networks.Computer Methods in Applied Mechanics and Engineering, 421:116813
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T18:32:51.753517Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation de9ca75e-989e-41b8-9490-4050da559552 · outbound
This paper cites Exact enforcement of temporal continuity in sequential physics-informed neural networks.Computer Methods in Applied Mechanics and Engineering, 430:117197.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Exact enforcement of temporal continuity in sequential physics-informed neural networks.Computer Methods in Applied Mechanics and Engineering, 430:117197
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T18:32:51.862819Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation 3e7ad9e3-98b6-4207-9755-76af6ac8990e · outbound
This paper cites Convergence analysis of pseudo-transient continuation.SIAM Journal on Numerical Analysis, 35(2):508–523.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Convergence analysis of pseudo-transient continuation.SIAM Journal on Numerical Analysis, 35(2):508–523
Reference 50
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T18:32:51.742031Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation 0bd4c7e2-ec8a-479b-a2e8-c91e9018fae0 · outbound
This paper cites TSONN: Time-stepping-oriented neural network for solving partial differential equations.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions TSONN: Time-stepping-oriented neural network for solving partial differential equations
Reference 51
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T21:06:14.620975Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation 8dae5a37-0709-4a23-a08e-053a31446a7a · outbound
This paper cites A pseudo-time stepping and parameterized physics-informed neural network framework for navier–stokes equations.Physics of Fluids, 37(3).
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions A pseudo-time stepping and parameterized physics-informed neural network framework for navier–stokes equations.Physics of Fluids, 37(3)
Reference 52
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T18:32:51.871290Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation 9da11ce1-cdda-44f1-8b7b-bf975f066773 · outbound
This paper cites Two-point step size gradient methods.IMA journal of numerical analysis, 8(1):141–148.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Two-point step size gradient methods.IMA journal of numerical analysis, 8(1):141–148
Reference 53
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T18:32:51.932847Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation 15a761ad-10a7-4df9-a1cf-1eebebe477ab · outbound
This paper cites SIAM.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions SIAM
Reference 54
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T18:32:51.867139Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation b6124f7c-4947-40d9-9a35-86ecd5bd8fca · outbound
This paper cites About modifications of the loss function for the causal training of physics- informed neural networks.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions About modifications of the loss function for the causal training of physics- informed neural networks
Reference 55
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T18:32:51.815036Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation 43e53be1-2960-4781-970c-3b04c91416f4 · outbound
This paper cites Fp64 is all you need: rethinking failure modes in physics-informed neural networks.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Fp64 is all you need: rethinking failure modes in physics-informed neural networks
Reference 56
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T21:06:14.574482Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation 242aa55b-6aa3-4cce-8d24-f79af85820e7 · outbound
This paper cites Self-adaptive physics-informed neural networks.Journal of Computational Physics, 474:111722.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Self-adaptive physics-informed neural networks.Journal of Computational Physics, 474:111722
Reference 57
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T18:32:51.823377Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation 27710ca8-2b3b-4608-b2f4-6ce24eeac671 · outbound
This paper cites Optimizing the optimizer for physics-informed neural networks and kolmogorov-arnold networks.Computer Methods in Applied Mechanics and Engineering, 446:118308.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Optimizing the optimizer for physics-informed neural networks and kolmogorov-arnold networks.Computer Methods in Applied Mechanics and Engineering, 446:118308
Reference 58
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T18:32:51.954457Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation 3f970d8b-84ab-4496-a9af-16cab72471e2 · outbound
This paper cites Pseudotransient continuation and differential-algebraic equations.SIAM Journal on Scientific Computing, 25(2):553–569.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Pseudotransient continuation and differential-algebraic equations.SIAM Journal on Scientific Computing, 25(2):553–569
Reference 59
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T18:32:51.928948Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation c44797b0-6938-4672-a581-007ecb83b549 · outbound
This paper cites Surrogate modeling of multi-dimensional premixed and non-premixed combustion using pseudo-time stepping physics-informed neural networks.Physics of Fluids, 36(11).
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Surrogate modeling of multi-dimensional premixed and non-premixed combustion using pseudo-time stepping physics-informed neural networks.Physics of Fluids, 36(11)
Reference 60
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T18:32:51.886203Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation b760415e-7dc4-4986-ae8a-29348d3e9d96 · outbound
This paper cites Scale- pinn: Learning efficient physics-informed neural networks through sequential correction.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Scale- pinn: Learning efficient physics-informed neural networks through sequential correction
Reference 61
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T21:06:14.628607Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation b8271ce2-766e-4919-b409-e3cd4e6a8bd4 · outbound
This paper cites Bridging computational fluid dynamics algorithm and physics-informed learning: Simple-pinn for incompressible navier- stokes equations.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Bridging computational fluid dynamics algorithm and physics-informed learning: Simple-pinn for incompressible navier- stokes equations
Reference 62
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T21:06:14.593257Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation 85b28e60-f0ab-4118-9a6e-a7c75a489d61 · outbound
This paper cites SOAP: Improving and Stabilizing Shampoo using Adam.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions SOAP: Improving and Stabilizing Shampoo using Adam
Reference 63
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T01:02:28.631723Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation 84d42333-0258-4615-bdda-97d98c3a9a77 · outbound
This paper cites An Expert's Guide to Training Physics-informed Neural Networks.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions An Expert's Guide to Training Physics-informed Neural Networks
Reference 64
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T21:06:14.649817Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation e22f3e4f-e7bd-488d-902b-b865d145ec24 · outbound
This paper cites A method for representing periodic functions and enforcing exactly periodic boundary conditions with deep neural networks.Journal of Computational Physics, 435:110242.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions A method for representing periodic functions and enforcing exactly periodic boundary conditions with deep neural networks.Journal of Computational Physics, 435:110242
Reference 65
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T18:32:51.745870Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation 46104e5e-5299-40af-9432-9762ebf385c2 · outbound
This paper cites Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains
Reference 66
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-11T21:06:14.634335Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation 38744bfe-129a-479f-97a0-54e161581534 · outbound
This paper cites Adam: A Method for Stochastic Optimization.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Adam: A Method for Stochastic Optimization
Reference 67
- Resolution
- verified exact
- local_arxiv, observed 2026-05-11T21:06:14.655586Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation a7f1b7d0-2ac6-4508-bf75-1a21fc3b362b · outbound
This paper cites Chebfun guide.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Chebfun guide
Reference 68
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T18:32:51.854593Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation 5da0f803-0838-4116-9a67-efcd6650b8b5 · outbound
This paper cites Ketcheson, Kyle T.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Ketcheson, Kyle T
Reference 69
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T18:32:51.834451Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation a8ced3ec-0202-4dff-840d-b416a195a829 · outbound
This paper cites Economon, Francisco Palacios, Sean R.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Economon, Francisco Palacios, Sean R
Reference 70
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T18:32:51.838279Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation 5b313ef7-e40f-407f-88c2-c820bb6d232e · outbound
This paper cites Bezgin, Aaron B.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Bezgin, Aaron B
Reference 71
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-26T18:32:51.830806Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation 9aa719ea-c56a-4ea4-a81e-47b1125b24fd · outbound
This paper cites solitons.
When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions solitons
Reference 72
- Resolution
- malformed identifier
- raw_fallback, observed 2026-05-26T18:32:51.790169Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Pith citing papers
Observation 4b0a8036-57af-4fa5-9f27-cd8e4a68945f · inbound
On the training of physics-informed neural operators for solving parametric partial differential equations cites this paper.
On the training of physics-informed neural operators for solving parametric partial differential equations When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions
Reference 78
- Resolution
- malformed identifier
- local_arxiv, observed 2026-07-02T11:36:55.278389Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation c7772b9b-d994-4e65-af3d-5276eb0082a8 · inbound
Generalizable turbulence closures across bluff-body shapes by PINN-based solver-agnostic training cites this paper.
Generalizable turbulence closures across bluff-body shapes by PINN-based solver-agnostic training When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-07-11T18:42:52.971866Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bae237ce-4f9d-4593-8105-d2ce25fdae00 · inbound
Generalizable turbulence closures across bluff-body shapes by PINN-based solver-agnostic training cites this paper.
Generalizable turbulence closures across bluff-body shapes by PINN-based solver-agnostic training When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-07-13T06:59:52.656435Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.