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DTSTART:19700308T020000
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DTSTAMP:20260417T190156Z
LOCATION:West Building\, Rooms 101-102
DTSTART;TZID=America/Los_Angeles:20250812T134000
DTEND;TZID=America/Los_Angeles:20250812T144000
UID:siggraph_SIGGRAPH 2025_sess542_ind_164@linklings.com
SUMMARY:Building ML Pipelines in Houdini
DESCRIPTION:This presentation shows you how to build supervised ML pipelin
 es in Houdini 21.\n\nWe give an overview of many of the ML nodes that are 
 available in Houdini, where special attention is given to nodes and featur
 es that have been added with Houdini 21.\nThese ML nodes are designed to b
 oth leverage and enhance Houdini's proceduralism.\nFully automated end-to-
 end ML pipelines that include data generation, training and inference can 
 be built entirely inside Houdini.\n\nHoudini's ML nodes can be used to per
 form sub-tasks that are common to a variety of machine learning applicatio
 ns. This can save you a lot of work when you're creating your own machine 
 learning pipeline. Among other things, the ML nodes support example genera
 tion, preprocessing, saving & loading data sets, neural-network training, 
 and inference.\n\nWe show how the ML nodes were used to build ML applicati
 ons that are being released as part of Houdini 21. These applications incl
 ude a volume upresser that can be applied to pyro sims and an improved cha
 racter deformer.\n\nInterest Area: New Technologies, Production & Animatio
 n, Research & Education\n\nKeyword: Animation, Artificial Intelligence/Mac
 hine Learning, Dynamics, Pipeline Tools and Work, Simulation\n\nRegistrati
 on Category: Full Conference, Experience, Exhibits Only, Tuesday\n\n
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