Learning lagrangian fluid mechanics with e (3)-equivariant graph neural networks AP Toshev, G Galletti, J Brandstetter, S Adami, NA Adams International Conference on Geometric Science of Information, 332-341, 2023 | 4 | 2023 |
Lagrangebench: A lagrangian fluid mechanics benchmarking suite A Toshev, G Galletti, F Fritz, S Adami, N Adams Advances in Neural Information Processing Systems 36, 2024 | 2 | 2024 |
On the relationships between graph neural networks for the simulation of physical systems and classical numerical methods AP Toshev, L Paehler, A Panizza, NA Adams arXiv preprint arXiv:2304.00146, 2023 | 2 | 2023 |
Neural SPH: Improved Neural Modeling of Lagrangian Fluid Dynamics AP Toshev, JA Erbesdobler, NA Adams, J Brandstetter arXiv preprint arXiv:2402.06275, 2024 | 1 | 2024 |
JAX-SPH: A Differentiable Smoothed Particle Hydrodynamics Framework AP Toshev, H Ramachandran, JA Erbesdobler, G Galletti, J Brandstetter, ... arXiv preprint arXiv:2403.04750, 2024 | | 2024 |
Accelerating Molecular Graph Neural Networks via Knowledge Distillation F Ekström Kelvinius, D Georgiev, A Toshev, J Gasteiger Advances in Neural Information Processing Systems 36, 2024 | | 2024 |
Accelerating Molecular Graph Neural Networks via Knowledge Distillation FE Kelvinius, D Georgiev, AP Toshev, J Gasteiger arXiv preprint arXiv:2306.14818, 2023 | | 2023 |
E() Equivariant Graph Neural Networks for Particle-Based Fluid Mechanics AP Toshev, G Galletti, J Brandstetter, S Adami, NA Adams arXiv preprint arXiv:2304.00150, 2023 | | 2023 |