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TZID:Asia/Tokyo
X-LIC-LOCATION:Asia/Tokyo
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TZOFFSETFROM:+0900
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DTSTART:18871231T000000
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BEGIN:VEVENT
DTSTAMP:20250110T023309Z
LOCATION:Hall B5 (1)\, B Block\, Level 5
DTSTART;TZID=Asia/Tokyo:20241203T144500
DTEND;TZID=Asia/Tokyo:20241203T145600
UID:siggraphasia_SIGGRAPH Asia 2024_sess106_papers_387@linklings.com
SUMMARY:Differential Walk on Spheres
DESCRIPTION:Technical Papers\n\nBailey Miller (Carnegie Mellon Uniersity),
  Rohan Sawhney (NVIDIA), and Keenan Crane and Ioannis Gkioulekas (Carnegie
  Mellon Uniersity)\n\nWe introduce a Monte Carlo method for computing deri
 vatives of the solution to a partial differential equation (PDE) with resp
 ect to problem parameters (such as domain geometry or boundary conditions)
 . Derivatives can be evaluated at arbitrary points, without performing a g
 lobal solve or constructing a volumetric grid or mesh. The method is hence
  well suited to inverse problems with complex geometry, such as PDE-constr
 ained shape optimization. Like other walk on spheres (WoS) algorithms, our
  method is trivial to parallelize, and is agnostic to boundary representat
 ion (meshes, splines, implicit surfaces, etc.), supporting large topologic
 al changes.  We focus in particular on screened Poisson equations, which m
 odel diverse problems from scientific and geometric computing.  As in diff
 erentiable rendering, we jointly estimate derivatives with respect to all 
 parameters---hence, cost does not grow significantly with parameter count.
   In practice, even noisy derivative estimates exhibit fast, stable conver
 gence for stochastic gradient-based optimization, as we show through examp
 les from thermal design, shape from diffusion, and computer graphics.\n\nR
 egistration Category: Full Access, Full Access Supporter\n\nLanguage Forma
 t: English Language\n\nSession Chair: Yonghao Yue (Aoyama Gakuin Universit
 y)
URL:https://asia.siggraph.org/2024/program/?id=papers_387&sess=sess106
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