Geometric Graph Representations and Geometric Graph Convolutions for Deep Learning on Three-Dimensional (3D) Graphs

2 June 2020

Papers citing "Geometric Graph Representations and Geometric Graph Convolutions for Deep Learning on Three-Dimensional (3D) Graphs"

7 / 7 papers shown

Title
Bayesian Hyperparameter Optimization with BoTorch, GPyTorch and Ax Daniel T. Chang BDL AI4CE 28 11 0 11 Dec 2019
BoTorch: A Framework for Efficient Monte-Carlo Bayesian Optimization Maximilian Balandat Brian Karrer Daniel R. Jiang Sam Daulton Benjamin Letham A. Wilson E. Bakshy 61 93 0 14 Oct 2019
A Generative Model for Molecular Distance Geometry G. Simm José Miguel Hernández-Lobato GAN 77 108 0 25 Sep 2019
Fast Graph Representation Learning with PyTorch Geometric Matthias Fey J. E. Lenssen 3DH GNN 3DPC 237 4,364 0 06 Mar 2019
Three-Dimensionally Embedded Graph Convolutional Network (3DGCN) for Molecule Interpretation Hyeoncheol Cho I. Choi 61 56 0 24 Nov 2018
A Tutorial on Bayesian Optimization P. Frazier GP 113 1,794 0 08 Jul 2018
Practical Bayesian Optimization of Machine Learning Algorithms Jasper Snoek Hugo Larochelle Ryan P. Adams 373 7,957 0 13 Jun 2012