← authors · overview

• Learning two-phase microstructure evolution using neural operators and autoencoder architectures
  2022 · 130 citations
• A comprehensive and FAIR comparison between MLP and KAN representations for differential equations and operator networks
  2024 · 125 citations
• Scalable algorithms for physics-informed neural and graph networks
  2022 · 49 citations
• Optimizing the Optimizer for Physics-Informed Neural Networks and Kolmogorov-Arnold Networks
  2025 · 29 citations
• A Framework Based on Symbolic Regression Coupled with eXtended Physics-Informed Neural Networks for Gray-Box Learning of Equations of Motion from Data
  2023 · 26 citations
• Tackling the Curse of Dimensionality with Physics-Informed Neural Networks
  2023 · 17 citations
• A physics-informed neural network for quantifying the microstructure properties of polycrystalline Nickel using ultrasound data
  2021 · 10 citations
• AI-Aristotle: A Physics-Informed framework for Systems Biology Gray-Box Identification
  2023 · 3 citations
• Characterization of partial wetting by CMAS droplets using multiphase many-body dissipative particle dynamics and data-driven discovery based on PINNs
  2023 · 2 citations
• Rethinking materials simulations: Blending direct numerical simulations with neural operators
  2023 · 2 citations