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Symbolic Graph Networks for Robust PDE Discovery from Noisy Sparse Data

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1 SIGNALFIRST DETECTED 26 March 2026
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26 Mar
Sparsely-Supervised Data Assimilation via Physics-Informed Schr\"odinger Bridge

arXiv:2603.22319v1 Announce Type: cross Abstract: Data assimilation (DA) for systems governed by partial differential equations (PDE) aims to reconstruct full spatiotemporal

REPORT · HOW · ArXiv CS.AIOPEN STORY
31 Aug
See, Hypothesize, Validate: Multimodal Agentic Framework for Discovering Governing PDEs

arXiv:2608.27869v1 Announce Type: new Abstract: Discovering governing partial differential equations (PDEs) from observational data remains a core challenge across the sciences.

REPORT · WHAT · ArXiv CS.AIOPEN STORY
30 Apr
Momentum-Conserving Graph Neural Networks for Deformable Objects

arXiv:2604.26097v1 Announce Type: cross Abstract: Graph neural networks (GNNs) have emerged as a versatile and efficient option for modeling the dynamic behavior of deformable

REPORT · WHAT · ArXiv CS.AIOPEN STORY
6 Oct
Training Numerical Intelligence via Auto-Diagnosis and Skill Discovery

arXiv:2610.03872v1 Announce Type: new Abstract: AI agents are becoming increasingly capable of generating scientific code, but generating code is not the same as improving the

REPORT · HOW · ArXiv CS.AIOPEN STORY
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