Skip to content
Log in
Sponsored Artificial Intelligence: A Modern Approach, Global Edition Artificial Intelligence: A Modern Approach, Global Edition

Author

M. Esmaeilbeigi

h-index 3 View on Semantic Scholar

We have 2 of 7 papers

We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.

Not the right person? Other researchers publish under this name.

Review Open access Aug 2026

Advancements and Future Directions in Loss Function Designs for Physics-Informed Neural Networks: A Comprehensive Review

This review synthesizes recent advances in loss function designs for Physics-Informed Neural Networks (PINNs), a transformative approach to solving partial differential equations (PDEs) by embedding physical laws into deep learning frameworks, to equip researchers with insights to refine PINN methodologies.

M. Esmaeilbeigi, Daniela Annunziata, Salvatore Cuomo et al. · 0 citations
Review Open access Aug 2026

Advancements and Future Directions in Loss Function Designs for Physics-Informed Neural Networks: A Comprehensive Review

This review synthesizes recent advances in loss function designs for Physics-Informed Neural Networks (PINNs), a transformative approach to solving partial differential equations (PDEs) by embedding physical laws into deep learning frameworks. We begin by exploring the foundational role of loss functions in deep neural...

M. Esmaeilbeigi, Daniela Annunziata, Salvatore Cuomo et al. · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.