16 citations · 23 across the 8 of their papers we have counts for
4 papers · 1 filter
Geometry Meets Physics: Data-Efficient Pre-Training for Unstructured Neural PDE Solvers
Luis Medrano-Navarro, Giacomo Baldan, Qiang Liu +4
Neural surrogate models for Partial Differential Equations (PDEs) on unstructured 3D geometries are often limited by poor generalization and the high cost of generating large-scale…
StocBench: A Benchmark for Generative Modeling of Stochastic Dynamics
Sebastian Pfister, Benjamin Holzschuh, Nils Thuerey
We benchmark transport-based generative models as well as distillation-based few-step methods for the probabilistic forecasting of stochastic fluid flows, with a particular focus o…
Shieldstral
Antonia Calvi, Avinash Sooriyarachchi, Giada Pistilli +273
We introduce Shieldstral, a 3B-parameter policy-adaptive multimodal safety classifier that matches or outperforms models nearly 7 its size on text safety benchmarks and set…
Tadpole: Autoencoders as Foundation Models for 3D PDEs with Online Learning
Qiang Liu, Felix Koehler, Benjamin Holzschuh +1
We introduce Tadpole, a novel foundation model for three-dimensional partial differential equations (PDEs) that addresses key challenges in transferability, scalability to high dim…