Search Results for author:
Found 3 papers, 2 papers with code
Fluid Dynamics Network: Topology-Agnostic 4D Reconstruction via Fluid Dynamics Priors
Representing 3D surfaces as level sets of continuous functions over $\mathbb{R}^3$ is the common denominator of neural implicit representations, which recently enabled remarkable progress in geometric deep learning and computer vision tasks.
SBML2Modelica: integrating biochemical models within open-standard simulation ecosystems
Modelica is one of the most popular existing open-standard general-purpose simulation languages, supported by many simulators.
Learning Spectral Unions of Partial Deformable 3D Shapes
Spectral geometric methods have brought revolutionary changes to the field of geometry processing.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
