activity
20182022
most citedHigh-order Differentiable Autoencoder for Nonlinear Model Reduction

4 citations · 11 across the 7 of their papers we have counts for

collaborators

15 papers

cs.AI2022

TPA-Net: Generate A Dataset for Text to Physics-based Animation

Yuxing Qiu, Feng Gao, Minchen Li +3

Recent breakthroughs in Vision-Language (V&L) joint research have achieved remarkable results in various text-driven tasks. High-quality Text-to-video (T2V), a task that has been l…

cs.RO20223 cited

Midas: A Multi-Joint Robotics Simulator with Intersection-Free Frictional Contact

Yunuo Chen, Minchen Li, Wenlong Lu +2

We introduce Midas, a robotics simulation framework based on the Incremental Potential Contact (IPC) model. Our simulator guarantees intersection-free, stable, and accurate resolut…

cs.GR2022

Affine Body Dynamics: Fast, Stable & Intersection-free Simulation of Stiff Materials

Lei Lan, Danny M. Kaufman, Minchen Li +2

Simulating stiff materials in applications where deformations are either not significant or can safely be ignored is a pivotal task across fields. Rigid body modeling has thus long…

cs.GR2021

Ships, Splashes, and Waves on a Vast Ocean

Libo Huang, Ziyin Qu, Xun Tan +3

The simulation of large open water surface is challenging using a uniform volumetric discretization of the Navier-Stokes equations. Simulating water splashes near moving objects, w…

cs.LG20214 cited

High-order Differentiable Autoencoder for Nonlinear Model Reduction

Siyuan Shen, Yang Yin, Tianjia Shao +4

This paper provides a new avenue for exploiting deep neural networks to improve physics-based simulation. Specifically, we integrate the classic Lagrangian mechanics with a deep au…

cs.GR2020

Codimensional Incremental Potential Contact

Minchen Li, Danny M. Kaufman, Chenfanfu Jiang

We extend the incremental potential contact (IPC) model for contacting elastodynamics to resolve systems composed of codimensional DOFs in arbitrary combination. This enables a uni…