activity
20172024
most citedGeometric Understanding of Deep Learning

34 citations · 139 across the 19 of their papers we have counts for

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Showing 2018Show all

7 papers · 1 filter

cs.CG2018★ 1 cited

Metric Based Quadrilateral Mesh Generation

Wei Chen, Xiaopeng Zheng, Jingyao Ke +3

This work proposes a novel metric based algorithm for quadrilateral mesh generating. Each quad-mesh induces a Riemannian metric satisfying special conditions: the metric is a flat…

cs.LG2018★ 2 cited

Latent Space Optimal Transport for Generative Models

Huidong Liu, Yang Guo, Na Lei +4

Variational Auto-Encoders enforce their learned intermediate latent-space data distribution to be a simple distribution, such as an isotropic Gaussian. However, this causes the pos…

cs.CG2018

Brain Morphometry Analysis with Surface Foliation Theory

Chengfeng Wen, Na Lei, Ming Ma +4

Brain morphometry study plays a fundamental role in neuroimaging research. In this work, we propose a novel method for brain surface morphometry analysis based on surface foliation…

cs.GR2018

The Normal Map Based on Area-Preserving Parameterization

Hui Zhao, Kehua Su, Ming Ma +3

In this paper, we present an approach to enhance and improve the current normal map rendering technique. Our algorithm is based on semi-discrete Optimal Mass Transportation (OMT) t…

cs.GR2018

Conformal Mesh Parameterization Using Discrete Calabi Flow

Hui Zhao, Xuan Li, Huabin Ge +2

In this paper, we introduce discrete Calabi flow to the graphics research community and present a novel conformal mesh parameterization algorithm. Calabi energy has a succinct and…

cs.GR2018★ 1 cited

Robust Edge-Preserved Surface Mesh Polycube Deformation

Hui Zhao, Na Lei, Xuan Li +3

The problem of polycube construction or deformation is an essential problem in computer graphics. In this paper, we present a robust, simple, efficient and automatic algorithm to d…

cs.LG2018★ 34 cited

Geometric Understanding of Deep Learning

Na Lei, Zhongxuan Luo, Shing-Tung Yau +1

Deep learning is the mainstream technique for many machine learning tasks, including image recognition, machine translation, speech recognition, and so on. It has outperformed conv…