Feb 1, 2022 · Our approach solves high-dimensional problems with complex physical dynamics, including designing surfaces and tools to manipulate fluid flows ...
Feb 1, 2022 · This work explores a simple, fast, and robust approach to inverse design which combines learned forward simulators based on graph neural ...
We show the evolution of designs across iterations for the gradient-based design optimization procedure across three tasks in the 2D Fluid Tools domain.
Our approach solves high-dimensional problems with complex physical dynamics, including designing surfaces and tools to manipulate fluid flows and optimizing ...
Our approach solveshigh-dimensional problems with complex physical dynamics, including designingsurfaces and tools to manipulate fluid flows and optimizing the ...
Our approach solves high-dimensional problems with complex physical dynamics, including designing surfaces and tools to manipulate fluid flows and optimizing ...
AK on X: "Physical Design using Differentiable Learned Simulators ...
twitter.com › _akhaliq › status
Feb 3, 2022 · Physical Design using Differentiable Learned Simulators abs: https://arxiv.org/abs/2202.00728. Embedded video. 0:07. 5:16 AM · Feb 3, 2022.
Jul 9, 2024 · This paper presents an in-depth review of the evolving landscape of differentiable physics simulators.
We take gradients through these learned simulators to optimize physical designs for a variety of tasks without further fine-tuning. This method can create 2D ...
Duration: 30:00
Posted: Feb 21, 2021
Posted: Feb 21, 2021
Missing: Design | Show results with:Design