Scalable Geometric Deep Learning on Molecular Graphs

6 December 2021

Papers citing "Scalable Geometric Deep Learning on Molecular Graphs"

6 / 6 papers shown

Title
Reducing Down(stream)time: Pretraining Molecular GNNs using Heterogeneous AI Accelerators Jenna A. Bilbrey Kristina M Herman Henry W Sprueill Soritis S. Xantheas Payel Das Manuel Lopez Roldan Mike Kraus Hatem Helal Sutanay Choudhury AI4CE 21 4 0 08 Nov 2022
Benchmarking Resource Usage for Efficient Distributed Deep Learning Nathan C. Frey Baolin Li Joseph McDonald Dan Zhao Michael Jones David Bestor Devesh Tiwari V. Gadepally S. Samsi 32 9 0 28 Jan 2022
Bringing Atomistic Deep Learning to Prime Time Nathan C. Frey S. Samsi Bharath Ramsundar Connor W. Coley V. Gadepally AI4CE 22 0 0 09 Dec 2021
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges M. Bronstein Joan Bruna Taco S. Cohen Petar Velivcković GNN 174 1,106 0 27 Apr 2021
Benchmarking Graph Neural Networks Vijay Prakash Dwivedi Chaitanya K. Joshi Anh Tuan Luu T. Laurent Yoshua Bengio Xavier Bresson 189 916 0 02 Mar 2020
Geometric deep learning: going beyond Euclidean data M. Bronstein Joan Bruna Yann LeCun Arthur Szlam P. Vandergheynst GNN 253 3,239 0 24 Nov 2016