Revisiting Transformation Invariant Geometric Deep Learning: Are Initial
Representations All You Need?

Revisiting Transformation Invariant Geometric Deep Learning: Are Initial Representations All You Need?

23 December 2021

Peng Cui

Papers citing "Revisiting Transformation Invariant Geometric Deep Learning: Are Initial Representations All You Need?"

4 / 4 papers shown

Title
Neural Combinatorial Optimization Algorithms for Solving Vehicle Routing Problems: A Comprehensive Survey with Perspectives Xuan Wu Di Wang Lijie Wen Yubin Xiao Chunguo Wu Yuesong Wu Chaoyu Yu D. Maskell You Zhou 68 4 0 01 Jun 2024
Representation Learning on Graphs with Jumping Knowledge Networks Keyulu Xu Chengtao Li Yonglong Tian Tomohiro Sonobe Ken-ichi Kawarabayashi Stefanie Jegelka GNN 267 1,944 0 09 Jun 2018
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation C. Qi Hao Su Kaichun Mo Leonidas J. Guibas 3DH 3DPC 3DV PINN 222 14,099 0 02 Dec 2016
Geometric deep learning: going beyond Euclidean data M. Bronstein Joan Bruna Yann LeCun Arthur Szlam P. Vandergheynst GNN 250 3,236 0 24 Nov 2016