We present a new method for implicit time integration of physical systems. Our approach
builds a bridge between nodal Finite Element methods and Position Based Dynamics …

We describe a scheme for time integration of mass-spring systems that makes use of a
solver based on block coordinate descent. This scheme provides a fast solution for classical …

We present a continuum-based discrete model for thin threads of viscous fluid by drawing
upon the Rayleigh analogy to elastic rods, demonstrating canonical coiling, folding, and …

We present a new method for real-time physics-based simulation supporting many different
types of hyperelastic materials. Previous methods such as Position-Based or Projective …

Abstract Implicit Neural Spatial Representation (INSR) has emerged as an effective
representation of spatially-dependent vector fields. This work explores solving time …

We introduce Neural Marching Cubes, a data-driven approach for extracting a triangle mesh
from a discretized implicit field. We base our meshing approach on Marching Cubes (MC) …

We introduce vertex block descent, a block coordinate descent solution for the variational
form of implicit Euler through vertex-level Gauss-Seidel iterations. It operates with local …

In this paper, we study the use of the Chebyshev semi-iterative approach in projective and
position-based dynamics. Although projective dynamics is fundamentally nonlinear, its …

Practical time steps in today's state-of-the-art simulators typically rely on Newton's method to
solve large systems of nonlinear equations. In practice, this works well for small time steps …

Learning workable representations of dynamical systems is becoming an increasingly
important problem in a number of application areas. By leveraging recent work connecting …