Towards Training Billion Parameter Graph Neural Networks for Atomic
Simulations

Towards Training Billion Parameter Graph Neural Networks for Atomic Simulations

18 March 2022

Brandon M. Wood

Siddharth Goyal

Papers citing "Towards Training Billion Parameter Graph Neural Networks for Atomic Simulations"

17 / 17 papers shown

Title
Distribution Learning for Molecular Regression Nima Shoghi Pooya Shoghi Anuroop Sriram Abhishek Das OOD 27 0 0 30 Jul 2024
Lightweight Geometric Deep Learning for Molecular Modelling in Catalyst Discovery Patrick Geitner GNN 28 0 0 05 Apr 2024
The Open DAC 2023 Dataset and Challenges for Sorbent Discovery in Direct Air Capture Anuroop Sriram Sihoon Choi Xiaohan Yu Logan M. Brabson Abhishek Das Zachary W. Ulissi Matthew Uyttendaele A. Medford D. Sholl AI4CE 27 35 0 01 Nov 2023
From Molecules to Materials: Pre-training Large Generalizable Models for Atomic Property Prediction Nima Shoghi Adeesh Kolluru John R. Kitchin Zachary W. Ulissi C. L. Zitnick Brandon M. Wood AI4CE 24 32 0 25 Oct 2023
LinGCN: Structural Linearized Graph Convolutional Network for Homomorphically Encrypted Inference Hongwu Peng Ran Ran Yukui Luo Jiahui Zhao Shaoyi Huang ... Tong Geng Chenghong Wang Xiaolin Xu Wujie Wen Caiwen Ding 27 36 0 25 Sep 2023
Accelerating Molecular Graph Neural Networks via Knowledge Distillation Filip Ekstrom Kelvinius D. Georgiev Artur P. Toshev Johannes Gasteiger 26 7 0 26 Jun 2023
EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations Yidong Liao Brandon M. Wood Abhishek Das Tess E. Smidt 24 131 0 21 Jun 2023
DR-Label: Improving GNN Models for Catalysis Systems by Label Deconstruction and Reconstruction Bo-Lan Wang Chen Liang Jiaze Wang Furui Liu Shaogang Hao Dong Li Jianye Hao Guangyong Chen Xiaolong Zou Pheng-Ann Heng 41 3 0 06 Mar 2023
The Open MatSci ML Toolkit: A Flexible Framework for Machine Learning in Materials Science Santiago Miret Kin Long Kelvin Lee Carmelo Gonzales Marcel Nassar Matthew Spellings 36 19 0 31 Oct 2022
Polyhistor: Parameter-Efficient Multi-Task Adaptation for Dense Vision Tasks Yen-Cheng Liu Chih-Yao Ma Junjiao Tian Zijian He Z. Kira 120 47 0 07 Oct 2022
Towards Sparsification of Graph Neural Networks Hongwu Peng Deniz Gurevin Shaoyi Huang Tong Geng Weiwen Jiang O. Khan Caiwen Ding GNN 30 24 0 11 Sep 2022
Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs Yi-Lun Liao Tess E. Smidt 80 215 0 23 Jun 2022
The Open Catalyst 2022 (OC22) Dataset and Challenges for Oxide Electrocatalysts Richard Tran Janice Lan Muhammed Shuaibi Brandon M. Wood Siddharth Goyal ... Jehad Abed Oleksandr Voznyy Edward H. Sargent Zachary W. Ulissi C. L. Zitnick 28 172 0 17 Jun 2022
Pre-training via Denoising for Molecular Property Prediction Sheheryar Zaidi Michael Schaarschmidt James Martens Hyunjik Kim Yee Whye Teh Alvaro Sanchez-Gonzalez Peter W. Battaglia Razvan Pascanu Jonathan Godwin DiffM AI4CE 15 121 0 31 May 2022
GemNet-OC: Developing Graph Neural Networks for Large and Diverse Molecular Simulation Datasets Johannes Gasteiger Muhammed Shuaibi Anuroop Sriram Stephan Günnemann Zachary W. Ulissi C. L. Zitnick Abhishek Das AI4TS MLAU 33 66 0 06 Apr 2022
The Open Catalyst 2020 (OC20) Dataset and Community Challenges L. Chanussot Abhishek Das Siddharth Goyal Thibaut Lavril Muhammed Shuaibi ... Brandon M. Wood Junwoong Yoon Devi Parikh C. L. Zitnick Zachary W. Ulissi 229 503 0 20 Oct 2020
Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism M. Shoeybi M. Patwary Raul Puri P. LeGresley Jared Casper Bryan Catanzaro MoE 245 1,817 0 17 Sep 2019