Publications

Welcome to the Publications section of LBMNet. This page presents our scientific contributions in the fields of Artificial Intelligence, Scientific Machine Learning, Physics-Inspired AI, Computer Vision, and the Lattice Boltzmann Method.

Our research aims to bridge mathematical modeling, computational physics, and deep learning to develop innovative AI architectures capable of solving complex scientific and engineering problems.

Journal Articles

  • A Lattice Boltzmann Method for Image Inpainting Inspired by Fluid Dynamics
Authors: Yassine Douich, et al.
Journal: European Journal of Pure and Applied Mathematics
Year: 2025
  • Eikonal equation solved with a novel Lattice Boltzmann method framework
Authors: Yassine Douich, et al.
Journal: Numerical Algorithms
Year:2026
  • Radial Basis Function Neural Networks for Collision Learning and Mask Detection in Image Inpainting
Authors: Yassine Douich, et al.
Conference paper:Communications in Computer and Information Science ((CCIS,volume 2817)).

Manuscripts Under Review


  • Neural Collision Learning for Image Inpainting via LBM Transport and CNN Mask Detection
Authors: Yassine Douich, et al.
Journal:Signal, Image and Video Processing.
Year:2026

  • An Artificial Intelligence Architecture Based on Lattice Boltzmann Dynamics for Image Inpainting
Authors: Yassine Douich, et al.
Journal:IEEE Transactions on Artificial Intelligence
Year:2026

  • From Convolution to Transport: A Lattice Boltzmann Reformulation of Deep Neural Networks
Authors: Yassine Douich, et al.
Journal: IEEE Access
Year:2026