publications

2026

1. Reduced-Order Operator Learning through Perceivers: Dissecting the Hidden Mechanisms

   S. Brivio, G. Kissas, A. Manzoni, and 1 more author

   2026

   To appear in the arXiv
2. METRO: Metric-Enhanced Token Routing Operator

   N. Koren, T. Hofmann, and G. Kissas

   2026

   Under Review NeurIPS 2026
3. Advectra: Asymmetric Latent Transport for Non-Stationary Physics

   N. Koren, T. Hofmann, and G. Kissas

   2026

   Under Review NeurIPS 2026
4. Attention, Generators, and Semigroups: Structurally Stable Deep Transformers

   G. Kissas, B. Bonev, O. Oikonomou, and 2 more authors

   2026

   Under Review NeurIPS 2026
5. Neuro-Symbolic ODE Discovery with Latent Grammar Flow

   K. Yu, E. Chatzi, and G. Kissas

   2026
6. Phaedra: Learning High-Fidelity Discrete Tokenization for the Physical Science

   L. Lingsch, G. Kissas, J. Jakubik, and 1 more author

   2026
7. Neuro-Symbolic AI for Analytical Solutions of Differential Equations

   O. Oikonomou, L. Lingsch, D. Grund, and 2 more authors

   In Forty-Third International Conference on Machine Learning, 2026
8. Accelerated Patient-Specific Calibration via Differentiable Hemodynamics Simulations

   D. Renner, S. Mishra, and G. Kissas

   2026

   Under Review ACM TOMS

2025

1. Grammar-based Ordinary Differential Equation Discovery

   K. Yu, E. Chatzi, and G. Kissas

   Mechanical Systems and Signal Processing, 2025
2. Reduced order computational fluid dynamic simulations in the thoracic aorta are associated with disease recorded in a medical biobank

   R. Sokolow, A. Bhattacharya, G. Kissas, and 8 more authors

   Scientific Reports, 2025

2024

1. FUSE: Fast Unified Simulation and Estimation for PDEs

   L. E. Lingsch, D. Grund, S. Mishra, and 1 more author

   In Thirty-eighth Conference on Neural Information Processing Systems, 2024
2. The Language of Hyperelastic Materials

   G. Kissas, S. Mishra, E. Chatzi, and 1 more author

   Computer Methods in Applied Mechanics and Engineering, 2024

2023

1. Variational Autoencoding Neural Operators

   J. H. Seidman, G. Kissas, G. J. Pappas, and 1 more author

   In International Conference on Machine Learning, 2023

2022

1. Learning Operators with Coupled Attention

   G. Kissas, J. H. Seidman, L. F. Guilhoto, and 3 more authors

   Journal of Machine Learning Research and Thirty-sixth Conference on Neural Information Processing Systems, Journal to Conference Track, 2022
2. NOMAD: Nonlinear Manifold Decoders for Operator Learning

   J. H. Seidman, G. Kissas, P. Perdikaris, and 1 more author

   In Thirty-sixth Conference on Neural Information Processing Systems, 2022

   Featured in the Paper of the Week section of DeepAI
3. Feasibility of Vascular Parameter Estimation for Assessing Hypertensive Pregnancy Disorders

   G. Kissas, E. Hwuang, E. W. Thompson, and 4 more authors

   Journal of Biomechanical Engineering, 2022
4. Scalable uncertainty quantification for deep operator networks using randomized priors

   Y. Yang, G. Kissas, and P. Perdikaris

   Computer Methods in Applied Mechanics and Engineering, 2022
5. Learning Operators with Coupled Attention

   G. Kissas, J. H. Seidman, L. F. Guilhoto, and 3 more authors

   Journal of Machine Learning Research, 2022

2020

1. Machine learning in cardiovascular flows modeling: Predicting arterial blood pressure from non-invasive 4D flow MRI data using physics-informed neural networks

   G. Kissas, Y. Yang, E. Hwuang, and 3 more authors

   Computer Methods in Applied Mechanics and Engineering, 2020

   Featured in the Most Cited Articles section of CMAME as one of the most cited papers of the years 2019-2023