Most Influential ArXiv (Analysis of PDEs) Papers (2026-04 Version)

2026-04-06 · Source: Resources | Paper Digest · Field: Science & Research — Mathematics & Computational Sciences, Artificial Intelligence & Machine Learning, Engineering & Applied Sciences · Depth: Expert, extended

Summary

This document presents Paper Digest's "Most Influential ArXiv (Analysis of PDEs) Papers" from 2018 to 2025, updated in April 2026. The ranking is automatically generated based on citations from both research papers and granted patents, highlighting up to 30 top papers annually within subfields like existence/uniqueness, boundary conditions, and various operators. Recurring themes among the influential papers include extensive research on nonlocal and fractional operators, Navier-Stokes and Schrödinger equations, regularity theory, and complex chemotaxis models. Paper Digest also offers a daily digest service and research tools for reading, writing, and literature reviews to aid professional knowledge discovery.

Key takeaway

This "Most Influential ArXiv (Analysis of PDEs) Papers (2026-04 Version)" provides a curated, frequently updated ranking of significant research in PDE analysis. Influence is automatically determined by citations from both research papers and granted patents, offering a robust measure of impact beyond traditional academic metrics. This resource is invaluable for professionals in science, technology, and specialized domains to quickly identify breakthroughs, conduct comprehensive literature reviews, and assess the real-world relevance of PDE research.

Topics

• Partial Differential Equations
• Nonlocal Operators
• Navier-Stokes Equations
• Schrödinger Equations
• Regularity Theory

Code references

• eshaghi-ms/vino
• crispitagorico/sigkernel
• paraklas/darcynets
• nathbo/egt

Best for: Research Scientist, AI Scientist

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Editorial summary, takeaway, and curation by AIssential. Original article published by Resources | Paper Digest.