81 citations · 329 across the 35 of their papers we have counts for
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Odd-DC: Generalizable Neural Model Reduction via Odd Difference-of-Convex Structure
Shixun Huang, Eitan Grinspun, Yue Chang
Model reduction is essential for real-time simulation of deformable objects. Linear techniques such as PCA provide structured and predictable behavior, but their limited expressive…
MorphModes: Non-rigid Registration via Adaptive Skinning Eigenmodes
Gabrielle Browne, Mengfei Liu, Eitan Grinspun +1
Non-rigid registration is a crucial task with applications in medical imaging, industrial robotics, computer vision, and entertainment. Standard approaches accomplish this task usi…
Topology-Preserving Coupling of Compressible Fluids and Thin Deformables
Jonathan Panuelos, Eitan Grinspun, David Levin
We present a novel discretization of coupled compressible fluid and thin deformable structures that provides sufficient and necessary leakproofness by preserving the path connected…
Force-Dual Modes: Subspace Design from Stochastic Forces
Otman Benchekroun, Eitan Grinspun, Maurizio Chiaramonte +1
Designing subspaces for Reduced Order Modeling (ROM) is crucial for accelerating finite element simulations in graphics and engineering. Unfortunately, it's not always clear which…
Precise Gradient Discontinuities in Neural Fields for Subspace Physics
Mengfei Liu, Yue Chang, Zhecheng Wang +2
Discontinuities in spatial derivatives appear in a wide range of physical systems, from creased thin sheets to materials with sharp stiffness transitions. Accurately modeling these…
Script2Screen: Supporting Dialogue Scriptwriting with Interactive Audiovisual Generation
Zhecheng Wang, Jiaju Ma, Eitan Grinspun +2
Scriptwriting has traditionally been text-centric, a modality that only partially conveys the produced audiovisual experience. A formative study with professional writers informed…
Fast Subspace Fluid Simulation with a Temporally-Aware Basis
Siyuan Chen, Yixin Chen, Jonathan Panuelos +4
We present a novel reduced-order fluid simulation technique leveraging Dynamic Mode Decomposition (DMD) to achieve fast, memory-efficient, and user-controllable subspace simulation…
Lifting the Winding Number: Precise Discontinuities in Neural Fields for Physics Simulation
Yue Chang, Mengfei Liu, Zhecheng Wang +2
Cutting thin-walled deformable structures is common in daily life, but poses significant challenges for simulation due to the introduced spatial discontinuities. Traditional method…