Robuta

Abstract page for arXiv paper 2408.10011: PinnDE: Physics-Informed Neural Networks for Solving Differential Equations

This free textbook is an OpenStax resource written to increase student access to high-quality, peer-reviewed learning materials.

This free textbook is an OpenStax resource written to increase student access to high-quality, peer-reviewed learning materials.

This free textbook is an OpenStax resource written to increase student access to high-quality, peer-reviewed learning materials.

This free textbook is an OpenStax resource written to increase student access to high-quality, peer-reviewed learning materials.

Abstract page for arXiv paper physics/0102063: Equations relating structure functions of all orders

This paper proposes a new way to learn Physics-Informed Neural Network loss functions using Generalized Additive Models. We apply our method by

Abstract page for arXiv paper 2507.18346: Low-rank adaptive physics-informed HyperDeepONets for solving differential equations

This free textbook is an OpenStax resource written to increase student access to high-quality, peer-reviewed learning materials.

McCauley's book described as an innovative contribution to field of mathematical finance theory.

This free textbook is an OpenStax resource written to increase student access to high-quality, peer-reviewed learning materials.

Abstract page for arXiv paper 2103.13878: A Physics-Informed Neural Network Framework For Partial Differential Equations on 3D Surfaces: Time-Dependent Problems

AI Model Successfully Generates Valid Particle Physics Equations While Preserving Core Physical Laws. Tagged with machinelearning, ai, programming, datascience.