Partial Differential Equations and Applications

Aims & Scope

Partial Differential Equations and Applications (PDEA) offers a single platform for all PDE-based research, bridging the areas of Mathematical Analysis, Computational Mathematics and applications of Mathematics in the Sciences.

It thus encourages and amplifies the transfer of knowledge between scientists with different backgrounds and from different disciplines who study, solve or apply the same types of equations.

PDEA accepts both original research as well as review articles of high quality, providing thorough and fast peer-review.

View Aims & Scope

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Metrics & Ranking

Impact Factor

Year	Value
2025	1.6

SJR (SCImago Journal Rank)

Year	Value
2024	0.531

Quartile

Year	Value
2024	Q2

h-index

Year	Value
2024	9

Journal Rank

Year	Value
2024	10956

Journal Citation Indicator

Year	Value
2024	196

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Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar
• Web of Science

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Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Mathematics, designed to support cutting-edge academic discovery.

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Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• A proof that rectified deep neural networks overcome the curse of dimensionality in the numerical approximation of semilinear heat equations

  Citation: 68

  Authors: Martin, Arnulf, Thomas, Tuan Anh

• Normalized solutions for a class of nonlinear Choquard equations

  Citation: 55

  Authors: Thomas, Yanyan, Zhaoli

• Solving high-dimensional Hamilton–Jacobi–Bellman PDEs using neural networks: perspectives from the theory of controlled diffusions and measures on path space

  Citation: 29

  Authors: Nikolas, Lorenz

• Multilevel Picard iterations for solving smooth semilinear parabolic heat equations

  Citation: 23

  Authors: Weinan, Martin, Arnulf, Thomas

• Neural networks-based backward scheme for fully nonlinear PDEs

  Citation: 23

  Authors: Huyên, Xavier, Maximilien

• Deep learning schemes for parabolic nonlocal integro-differential equations

  Citation: 14

  Authors: Javier

• Decay in the one dimensional generalized Improved Boussinesq equation

  Citation: 14

  Authors: Christopher, Claudio

• (Non-)convergence of solutions of the convective Allen–Cahn equation

  Citation: 13

  Authors: Helmut

• Liouville type theorems for stationary Navier–Stokes equations

  Citation: 12

  Authors: Tai-Peng

• Deep neural network approximations for solutions of PDEs based on Monte Carlo algorithms

  Citation: 12

  Authors: Philipp, Arnulf, Diyora

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