Reducing Down(stream)time: Pretraining Molecular GNNs using Heterogeneous AI Accelerators

8 November 2022

Papers citing "Reducing Down(stream)time: Pretraining Molecular GNNs using Heterogeneous AI Accelerators"

7 / 7 papers shown

Title
ChemBERTa-2: Towards Chemical Foundation Models Walid Ahmad Elana Simon Seyone Chithrananda Gabriel Grand Bharath Ramsundar AI4CE 45 137 0 05 Sep 2022
Scalable Geometric Deep Learning on Molecular Graphs Nathan C. Frey S. Samsi Joseph McDonald Lin Li Connor W. Coley V. Gadepally GNN AI4CE 50 4 0 06 Dec 2021
Molformer: Motif-based Transformer on 3D Heterogeneous Molecular Graphs Fang Wu Dragomir R. Radev Huabin Xing ViT 56 57 0 04 Oct 2021
HydroNet: Benchmark Tasks for Preserving Intermolecular Interactions and Structural Motifs in Predictive and Generative Models for Molecular Data Sutanay Choudhury Jenna A. Bilbrey Logan T. Ward S. Xantheas Ian Foster Josef Heindel Ben Blaiszik Marcus Schwarting 54 3 0 30 Nov 2020
ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction Seyone Chithrananda Gabriel Grand Bharath Ramsundar AI4CE 75 406 0 19 Oct 2020
Strategies for Pre-training Graph Neural Networks Weihua Hu Bowen Liu Joseph Gomes Marinka Zitnik Percy Liang Vijay S. Pande J. Leskovec SSL AI4CE 108 1,401 0 29 May 2019
Fast Graph Representation Learning with PyTorch Geometric Matthias Fey J. E. Lenssen 3DH GNN 3DPC 214 4,334 0 06 Mar 2019