| 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 | 8 | 2024 |
| 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 | 8 | 2023 |
| Jax-sph: A differentiable smoothed particle hydrodynamics framework AP Toshev, H Ramachandran, JA Erbesdobler, G Galletti, J Brandstetter, ... arXiv preprint arXiv:2403.04750, 2024 | 7* | 2024 |
| 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 | 7 | 2023 |
| 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 | 6 | 2024 |
| Neural SPH: Improved Neural Modeling of Lagrangian Fluid Dynamics AP Toshev, JA Erbesdobler, NA Adams, J Brandstetter arXiv preprint arXiv:2402.06275, 2024 | 6 | 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 |
| Retro-Rank-In: A Ranking-Based Approach for Inorganic Materials Synthesis Planning T Prein, E Pan, S Haddouti, M Lorenz, J Jehkul, T Wilk, C Moran, ... arXiv preprint arXiv:2502.04289, 2025 | | 2025 |
| UPT++: Latent Point Set Neural Operators for Modeling System State Transitions A Fürst, F Sestak, AP Toshev, B Alkin, NA Adams, A Mayr, G Klambauer, ... | | |
Nikolaus AdamsProfessor für Aerodynamik und Strömungsmechanik, Technische Universität Münchenایمیل تأیید شده در tum.de
