Artur P. Toshev

According to our database, Artur P. Toshev authored at least 9 papers between 2021 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2025

LaM-SLidE: Latent Space Modeling of Spatial Dynamical Systems via Linked Entities.

Florian Sestak, Artur P. Toshev, Andreas Fürst, Günter Klambauer, Andreas Mayr, Johannes Brandstetter

CoRR, February, 2025

Retro-Rank-In: A Ranking-Based Approach for Inorganic Materials Synthesis Planning.

Thorben Prein, Elton Pan, Sami Haddouti, Marco Lorenz, Janik Jehkul, Tymoteusz Wilk, Cansu Moran, Menelaos Panagiotis Fotiadis, Artur P. Toshev, Elsa A. Olivetti, Jennifer L. M. Rupp

CoRR, February, 2025

2024

JAX-SPH: A Differentiable Smoothed Particle Hydrodynamics Framework.

Artur P. Toshev, Harish Ramachandran, Jonas A. Erbesdobler, Gianluca Galletti, Johannes Brandstetter, Nikolaus A. Adams

CoRR, 2024

Neural SPH: Improved Neural Modeling of Lagrangian Fluid Dynamics.

Artur P. Toshev, Jonas A. Erbesdobler, Nikolaus A. Adams, Johannes Brandstetter

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

E(3) Equivariant Graph Neural Networks for Particle-Based Fluid Mechanics.

Artur P. Toshev, Gianluca Galletti, Johannes Brandstetter, Stefan Adami, Nikolaus A. Adams

CoRR, 2023

On the Relationships between Graph Neural Networks for the Simulation of Physical Systems and Classical Numerical Methods.

Artur P. Toshev, Ludger Paehler, Andrea Panizza, Nikolaus A. Adams

CoRR, 2023

LagrangeBench: A Lagrangian Fluid Mechanics Benchmarking Suite.

Artur P. Toshev, Gianluca Galletti, Fabian Fritz, Stefan Adami, Nikolaus A. Adams

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Accelerating Molecular Graph Neural Networks via Knowledge Distillation.

Filip Ekström Kelvinius, Dimitar Georgiev, Artur P. Toshev, Johannes Gasteiger

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2021

Learning Lagrangian Fluid Mechanics with E(3)-Equivariant Graph Neural Networks.

Artur P. Toshev, Gianluca Galletti, Johannes Brandstetter, Stefan Adami, Nikolaus A. Adams

Proceedings of the Geometric Science of Information - 6th International Conference, 2021