Residual-based attention and connection to information bottleneck theory in PINNs. - Sokratis J. Anagnostopoulos; Juan Diego Toscano; Nikolaos Stergiopulos; George Em Karniadakis (CoRR, 2023)

Teeth Mold Point Cloud Completion Via Data Augmentation and Hybrid RL-GAN. - Juan Diego Toscano; Christian Zuniga-Navarrete; Wilson David Jo Siu; Luis Javier Segura; Hongyue Sun (J. Comput. Inf. Sci. Eng., 2023)

Learning in PINNs: Phase transition, total diffusion, and generalization. - Sokratis J. Anagnostopoulos; Juan Diego Toscano; Nikolaos Stergiopulos; George Em Karniadakis (CoRR, 2024)

A comprehensive and FAIR comparison between MLP and KAN representations for differential equations and operator networks. - Khemraj Shukla; Juan Diego Toscano; Zhicheng Wang; Zongren Zou; George Em Karniadakis (CoRR, 2024)

Inferring turbulent velocity and temperature fields and their statistics from Lagrangian velocity measurements using physics-informed Kolmogorov-Arnold Networks. - Juan Diego Toscano; Theo Käufer; Zhibo Wang; Martin Maxey; Christian Cierpka; George Em Karniadakis (CoRR, 2024)

From PINNs to PIKANs: Recent Advances in Physics-Informed Machine Learning. - Juan Diego Toscano; Vivek Oommen; Alan John Varghese; Zongren Zou; Nazanin Ahmadi Daryakenari; Chenxi Wu; George Em Karniadakis (CoRR, 2024)

KKANs: Kurková-Kolmogorov-Arnold networks and their learning dynamics. - Juan Diego Toscano; Li-Lian Wang; George Em Karniadakis (Neural Networks, 2025)

FMEnets: Flow, Material, and Energy networks for non-ideal plug flow reactor design. - Chenxi Wu; Juan Diego Toscano; Khemraj Shukla; Yingjie Chen; Ali Shahmohammadi; Edward Raymond; Thomas Toupy; Neda Nazemifard; Charles Papageorgiou; George Em Karniadakis (CoRR, 2025)

Explicit Construction of Approximate Kolmogorov-Arnold Superpositions with C2-Smoothness. - Lunji Song; Juan Diego Toscano; Li-Lian Wang (CoRR, 2025)