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Physics-informed neural ODE (PINODE): embedding physics into models using collocation points

Research article (Scientific Reports, 2023) · cited 48× · AI/ML
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Physics-informed neural ODE (PINODE): embedding physics into models using collocation points

Summary

Physics-informed neural ODE (PINODE): embedding physics into models using collocation points is a scholarly article[1].

Key Facts

  • Physics-informed neural ODE (PINODE): embedding physics into models using collocation points's instance of is recorded as scholarly article[2].

Related Entities

Aleksei Sholokhov

References

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Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

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Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.

APA 4ort.xyz Knowledge Graph. (2026). Physics-informed neural ODE (PINODE): embedding physics into models using collocation points. Retrieved May 24, 2026, from https://4ort.xyz/entity/physics-informed-neural-ode-pinode-embedding-physics-into-models-using-collocation-points
MLA “Physics-informed neural ODE (PINODE): embedding physics into models using collocation points.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/physics-informed-neural-ode-pinode-embedding-physics-into-models-using-collocation-points.
BibTeX @misc{4ortxyz_physics-informed-neural-ode-pinode-embedding-physics-into-models-using-collocation-points_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Physics-informed neural ODE (PINODE): embedding physics into models using collocation points}}, year = {2026}, url = {https://4ort.xyz/entity/physics-informed-neural-ode-pinode-embedding-physics-into-models-using-collocation-points}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Physics-informed neural ODE (PINODE): embedding physics into models using collocation points — https://4ort.xyz/entity/physics-informed-neural-ode-pinode-embedding-physics-into-models-using-collocation-points (retrieved 2026-05-24)

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