BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//132.216.98.100//NONSGML kigkonsult.se iCalcreator 2.20.4//
BEGIN:VEVENT
UID:20260728T182108EDT-0323D72Fp2@132.216.98.100
DTSTAMP:20260728T222108Z
DESCRIPTION:Abstract\n\nThe remarkable progress in graphics processing unit
 s over recent decades has given rise to a significant increase in the appl
 ication of computer graphics across various industries\, such as in cinema
  and video games. Consequently\, there has been a surge in opportunities t
 o push the boundaries of computer graphics algorithms\, leading to the dev
 elopment of highly intricate fluid simulations and photorealistic renderin
 g. These methods now serve as the foundation for AAA games\, animation fea
 tures\, and blockbuster movies.\n\nThis thesis emphasizes the development 
 and application of flexible Monte Carlo techniques for two specific subfie
 lds within computer graphics\, namely physically based rendering and fluid
  simulations. The rationale behind this focus is the shared similarities b
 etween the equations and mathematical models governing both domains\, pres
 enting an opportunity to bridge the gap between them and formulate new and
  effective methods. Moreover\, since the realism of a fluid simulation ren
 dering is inherently tied to the simulation itself\, and vice versa\, adva
 ncements in both areas are crucial for achieving maximum impact.\n\nFirst\
 , we present a versatile two-stage mutation strategy based on the delayed 
 rejection Markov chain Monte Carlo framework to generalize the Metropolis 
 light transport algorithm. By generating multiple proposals informed by pr
 evious failures while maintaining Markov chain ergodicity\, we can develop
  efficient strategies such as trying a cheap mutation first\, followed by 
 a more expensive one only upon failure. This approach allows for the optim
 al allocation of computational resources\, which is critical when tackling
  complex scenes.\n\nDrawing on the success of Monte Carlo methods in physi
 cally based rendering and\, more recently\, in discrete geometry processin
 g\, we propose a Monte Carlo approach for fluid simulations. Specifically\
 , we employ the Feynman–Kac stochastic representation of the vorticity tra
 nsport equation and devise a recursive Monte Carlo estimator of the\n\nBio
 t-Savart law that can generate pointwise approximate solutions. We expand 
 this method with a stream function formulation that enables us to manage f
 ree-slip boundary conditions using a Walk-on-Spheres algorithm. To our kno
 wledge\, this is the first time that Monte Carlo methods have been studied
  in the context of fluid simulations\, opening the door to a new family of
  solvers. We offer an in-depth examination of several potential directions
  for future research based on this novel numerical simulation modality.\n
DTSTART:20231026T140000Z
DTEND:20231026T160000Z
LOCATION:Room 603\, McConnell Engineering Building\, CA\, QC\, Montreal\, H
 3A 0E9\, 3480 rue University
SUMMARY:PhD defence of Damien Rioux-Lavoie – Flexible Monte Carlo Methods f
 or Fluid and Light Transport Simulations
URL:/ece/channels/event/phd-defence-damien-rioux-lavoi
 e-flexible-monte-carlo-methods-fluid-and-light-transport-simulations-35214
 5
END:VEVENT
END:VCALENDAR