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Hsueh-Ti Derek Liu - Towards Scalable Geometry Processing
Symposium on Geometry Processing 2022
[SGP 2022] TinyAD: Automatic Differentiation in Geometry Processing Made Simple
SGP 2020: Sparse Data Driven Mesh Deformation
Jens Agerberg: Teaching Neural Networks a Sense of Geometry
Structure-Aware Learning for Geometry Processing - Dr. Paul Guerrero
Geometry Processing in the Wild | Alec Jacobson | TEDxUofTSalon
PointFlow
[SIGGRAPH Asia 2026] Neural Field Processing on Surfaces
Generating Shapes as Distribution of Points
Learning Signal-Agnostic Manifolds of Neural Fields (NeurIPS 2021)
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Last Updated: September 30, 2026
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Summary
Join the Learning on Graphs and So welcome to this part of our workshop which covers the basics of May 18th, 2021 Abstract: Recent advances in 3D scanning technologies have brought us massive highly detailed TinyAD: Automatic Differentiation in Authors: Lin Gao (Institute of Computing Technology, Chinese Academy of Sciences) Yu-Kun Lai (Cardiff University) Jie Alec Jacobson will talk about how we create simulations from real world, messy data, and the complex applications of these ... A brief explanation of the paper "PointFlow: 3D Point Cloud Generation with Continuous Normalizing Flows". The supplementary video of Paper “ We present a generic method to capture the inherent manifold across any signal modality.
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