most citedA Survey of Geometric Optimization for Deep Learning: From Euclidean Space to Riemannian Manifold

2 citations · 3 across the 3 of their papers we have counts for

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cs.LG2023

CTAGE: Curvature-Based Topology-Aware Graph Embedding for Learning Molecular Representations

Yili Chen, Zhengyu Li, Zheng Wan +2

AI-driven drug design relies significantly on predicting molecular properties, which is a complex task. In current approaches, the most commonly used feature representations for tr…

cs.LG2023★ 2 cited

A Survey of Geometric Optimization for Deep Learning: From Euclidean Space to Riemannian Manifold

Yanhong Fei, Xian Wei, Yingjie Liu +2

Although Deep Learning (DL) has achieved success in complex Artificial Intelligence (AI) tasks, it suffers from various notorious problems (e.g., feature redundancy, and vanishing…