关注
Muhammed Shuaibi
Muhammed Shuaibi
Research Engineer, FAIR, Meta
在 meta.com 的电子邮件经过验证 - 首页
标题
引用次数
引用次数
年份
Open catalyst 2020 (OC20) dataset and community challenges
L Chanussot, A Das, S Goyal, T Lavril, M Shuaibi, M Riviere, K Tran, ...
Acs Catalysis 11 (10), 6059-6072, 2021
1522021
Rotation invariant graph neural networks using spin convolutions
M Shuaibi, A Kolluru, A Das, A Grover, A Sriram, Z Ulissi, CL Zitnick
arXiv preprint arXiv:2106.09575, 2021
292021
An introduction to electrocatalyst design using machine learning for renewable energy storage
CL Zitnick, L Chanussot, A Das, S Goyal, J Heras-Domingo, C Ho, W Hu, ...
arXiv preprint arXiv:2010.09435, 2020
292020
Forcenet: A graph neural network for large-scale quantum calculations
W Hu, M Shuaibi, A Das, S Goyal, A Sriram, J Leskovec, D Parikh, ...
arXiv preprint arXiv:2103.01436, 2021
212021
Enabling robust offline active learning for machine learning potentials using simple physics-based priors
M Shuaibi, S Sivakumar, RQ Chen, ZW Ulissi
Machine Learning: Science and Technology 2 (2), 025007, 2020
172020
The open catalyst 2022 (OC22) dataset and challenges for oxide electrocatalysis
R Tran, J Lan, M Shuaibi, S Goyal, BM Wood, A Das, J Heras-Domingo, ...
arXiv preprint arXiv:2206.08917, 2022
92022
How Do Graph Networks Generalize to Large and Diverse Molecular Systems?
J Gasteiger, M Shuaibi, A Sriram, S Günnemann, Z Ulissi, CL Zitnick, ...
arXiv e-prints, arXiv: 2204.02782, 2022
82022
Open Challenges in Developing Generalizable Large-Scale Machine-Learning Models for Catalyst Discovery
A Kolluru, M Shuaibi, A Palizhati, N Shoghi, A Das, B Wood, CL Zitnick, ...
ACS Catalysis 12 (14), 8572-8581, 2022
72022
Transfer learning using attentions across atomic systems with graph neural networks (TAAG)
A Kolluru, N Shoghi, M Shuaibi, S Goyal, A Das, CL Zitnick, Z Ulissi
The Journal of Chemical Physics 156 (18), 184702, 2022
62022
GemNet-OC: developing graph neural networks for large and diverse molecular simulation datasets
J Gasteiger, M Shuaibi, A Sriram, S Günnemann, Z Ulissi, CL Zitnick, ...
arXiv preprint arXiv:2204.02782, 2022
32022
AdsorbML: Accelerating Adsorption Energy Calculations with Machine Learning
J Lan, A Palizhati, M Shuaibi, BM Wood, B Wander, A Das, M Uyttendaele, ...
arXiv preprint arXiv:2211.16486, 2022
12022
Spherical Channels for Modeling Atomic Interactions
CL Zitnick, A Das, A Kolluru, J Lan, M Shuaibi, A Sriram, Z Ulissi, B Wood
arXiv preprint arXiv:2206.14331, 2022
12022
The Open Catalyst Challenge 2021: Competition Report
A Das, M Shuaibi, A Palizhati, S Goyal, A Grover, A Kolluru, J Lan, A Rizvi, ...
NeurIPS 2021 Competitions and Demonstrations Track, 29-40, 2022
2022
Generalizable Machine Learning Models for Electrocatalyst Discovery
M Shuaibi
Carnegie Mellon University, 2022
2022
Accelerating on-the-Fly Active Learning of Catalyst Simulations Using Large Scale Pretrained Models
J Musielewicz, M Shuaibi, Z Ulissi
2021 AIChE Annual Meeting, 2021
2021
An Active Learning Framework for Accelerating Saddle Point Searches Applied to Propylene Epoxidation
S Sivakumar, Z Ulissi, M Shuaibi, M Adams
2020 Virtual AIChE Annual Meeting, 2020
2020
The Open Catalyst Project Dataset
L Chanussot, A Das, J Heras-Domingo, S Goyal, C Ho, T Lavril, ...
2020 Virtual AIChE Annual Meeting, 2020
2020
ForceNet: A Graph Neural Network for Large-Scale Quantum Chemistry Simulation
W Hu, M Shuaibi, A Das, S Goyal, A Sriram, J Leskovec, D Parikh, ...
系统目前无法执行此操作,请稍后再试。
文章 1–18