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DTSTAMP:20260417T190158Z
LOCATION:West Building\, Rooms 211-214
DTSTART;TZID=America/Los_Angeles:20250813T154500
DTEND;TZID=America/Los_Angeles:20250813T155500
UID:siggraph_SIGGRAPH 2025_sess124_papers_679@linklings.com
SUMMARY:MIND: Microstructure INverse Design with Generative Hybrid Neural 
 Representation
DESCRIPTION:Tianyang Xue, Longdu Liu, and Lin Lu (Shandong University); Pa
 ul Henderson (University of Glasgow); Pengbin Tang (ETH Zürich); Haochen L
 i, Jikai Liu, and Haisen Zhao (Shandong University); Hao Peng (CrownCAD); 
 and Bernd Bickel (ETH Zürich)\n\nWe introduce MIND, a novel generative fra
 mework for inverse-designing diverse, tileable 3D microstructures. Leverag
 ing latent diffusion and our hybrid neural representation, MIND precisely 
 achieves targeted physical properties, ensures geometric validity, and ena
 bles seamless boundary compatibility—opening new avenues for advanced meta
 material design and manufacturing applications.\n\nInterest Area: Research
  & Education\n\nRecording: Livestreamed, Not Livestreamed, Recorded, Not R
 ecorded\n\nRegistration Category: Full Conference, Virtual Access, Wednesd
 ay\n\nSession Chair: Steve Marschner (Cornell University, NVIDIA)\n\n
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