Comparing recurrent and convolutional neural networks for predicting wave propagation. - Stathi Fotiadis; Eduardo Pignatelli; Mario Lino Valencia; Chris D. Cantwell; Amos J. Storkey; Anil A. Bharath (CoRR, 2020)

Simulating Surface Wave Dynamics with Convolutional Networks. - Mario Lino Valencia; Chris D. Cantwell; Stathi Fotiadis; Eduardo Pignatelli; Anil A. Bharath (CoRR, 2020)

Simulating Continuum Mechanics with Multi-Scale Graph Neural Networks. - Mario Lino; Chris D. Cantwell; Anil A. Bharath; Stathi Fotiadis (CoRR, 2021)

Disentangling ODE parameters from dynamics in VAEs. - Stathi Fotiadis; Mario Lino; Chris D. Cantwell; Anil A. Bharath (CoRR, 2021)

REMuS-GNN: A Rotation-Equivariant Model for Simulating Continuum Dynamics. - Mario Lino; Stathi Fotiadis; Anil A. Bharath; Chris D. Cantwell (TAG-ML, 2022)

Towards Fast Simulation of Environmental Fluid Mechanics with Multi-Scale Graph Neural Networks. - Mario Lino; Stathi Fotiadis; Anil A. Bharath; Chris D. Cantwell (CoRR, 2022)

Disentangled Generative Models for Robust Prediction of System Dynamics. - Stathi Fotiadis; Mario Lino Valencia; Shunlong Hu; Stef Garasto; Chris D. Cantwell; Anil Anthony Bharath (ICML, 2023)

Learning Distributions of Complex Fluid Simulations with Diffusion Graph Networks. - Mario Lino Valencia; Tobias Pfaff; Nils Thuerey (ICLR, 2025)