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DTSTAMP:20250522T212739Z
LOCATION:Bluebird Ballroom
DTSTART;TZID=America/Denver:20240728T180000
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UID:siggraph_SIGGRAPH 2024_sess211_papers_571@linklings.com
SUMMARY:Eulerian-Lagrangian Fluid Simulation on Particle Flow Maps
DESCRIPTION:Junwei Zhou (University of Michigan), Duowen Chen and Molin De
 ng (Georgia Institute of Technology), Yitong Deng (Stanford University), Y
 uchen Sun (Georgia Institute of Technology), Sinan Wang (University of Hon
 g Kong), Shiying Xiong (Zhejiang University), and Bo Zhu (Georgia Institut
 e of Technology)\n\nWe introduce Particle Flow Maps (PFM), a fluid simulat
 ion method outperforming Neural Flow Maps (NFM) in efficiency and maintain
 ing high accuracy. By leveraging particle trajectories and an Eulerian-Lag
 rangian framework, PFM achieves up to 49 times faster computation and 41\%
  less memory usage while better preserving vorticity in complex fluid dyna
 mics.\n\nInterest Area: Arts & Design, Production & Animation, Research & 
 Education\n\nRecording: Livestreamed, Recorded\n\nRegistration Category: F
 ull Conference, Full Conference Supporter, Virtual Access, Experience, Exh
 ibitor Full Conference, Exhibitor Experience, Sunday\n\n
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