Muhammed Shuaibi

According to our database, Muhammed Shuaibi authored at least 12 papers between 2020 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

AmpTorch: A Python package for scalable fingerprint-based neural network training on multi-element systems with integrated uncertainty quantification.

Muhammed Shuaibi, Yuge Hu, Xiangyun Lei, Benjamin M. Comer, Matt Adams, Jacob Paras, Rui Qi Chen, Eric Musa, Joseph Musielewicz, Andrew A. Peterson, Andrew J. Medford, Zachary W. Ulissi

J. Open Source Softw., 2023

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. Lawrence Zitnick, Abhishek Das

Trans. Mach. Learn. Res., 2022

AdsorbML: Accelerating Adsorption Energy Calculations with Machine Learning.

Janice Lan, Aini Palizhati, Muhammed Shuaibi, Brandon M. Wood, Brook Wander, Abhishek Das, Matt Uyttendaele, C. Lawrence Zitnick, Zachary W. Ulissi

CoRR, 2022

The Open Catalyst 2022 (OC22) Dataset and Challenges for Oxide Electrocatalysis.

Richard Tran, Janice Lan, Muhammed Shuaibi, Siddharth Goyal, Brandon M. Wood, Abhishek Das, Javier Heras-Domingo, Adeesh Kolluru, Ammar Rizvi, Nima Shoghi, Anuroop Sriram, Zachary W. Ulissi, C. Lawrence Zitnick

CoRR, 2022

How Do Graph Networks Generalize to Large and Diverse Molecular Systems?

Johannes Gasteiger, Muhammed Shuaibi, Anuroop Sriram, Stephan Günnemann, Zachary W. Ulissi, C. Lawrence Zitnick, Abhishek Das

CoRR, 2022

Spherical Channels for Modeling Atomic Interactions.

Larry Zitnick, Abhishek Das, Adeesh Kolluru, Janice Lan, Muhammed Shuaibi, Anuroop Sriram, Zachary W. Ulissi, Brandon M. Wood

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Enabling robust offline active learning for machine learning potentials using simple physics-based priors.

Muhammed Shuaibi, Saurabh Sivakumar, Rui Qi Chen, Zachary W. Ulissi

Mach. Learn. Sci. Technol., 2021

Rotation Invariant Graph Neural Networks using Spin Convolutions.

Muhammed Shuaibi, Adeesh Kolluru, Abhishek Das, Aditya Grover, Anuroop Sriram, Zachary W. Ulissi, C. Lawrence Zitnick

CoRR, 2021

ForceNet: A Graph Neural Network for Large-Scale Quantum Calculations.

Weihua Hu, Muhammed Shuaibi, Abhishek Das, Siddharth Goyal, Anuroop Sriram, Jure Leskovec, Devi Parikh, C. Lawrence Zitnick

CoRR, 2021

The Open Catalyst Challenge 2021: Competition Report.

Abhishek Das, Muhammed Shuaibi, Aini Palizhati, Siddharth Goyal, Aditya Grover, Adeesh Kolluru, Janice Lan, Ammar Rizvi, Anuroop Sriram, Brandon M. Wood, Devi Parikh, Zachary W. Ulissi, C. Lawrence Zitnick, Guolin Ke, Shuxin Zheng, Yu Shi, Di He, Tie-Yan Liu, Chengxuan Ying, Jiacheng You, Yihan He, Rostislav Grigoriev, Ruslan Lukin, Adel Yarullin, Max Faleev

Proceedings of the NeurIPS 2021 Competitions and Demonstrations Track, 2021

2020

The Open Catalyst 2020 (OC20) Dataset and Community Challenges.

Lowik Chanussot, Abhishek Das, Siddharth Goyal, Thibaut Lavril, Muhammed Shuaibi, Morgane Riviere, Kevin Tran, Javier Heras-Domingo, Caleb Ho, Weihua Hu, Aini Palizhati, Anuroop Sriram, Brandon M. Wood, Junwoong Yoon, Devi Parikh, C. Lawrence Zitnick, Zachary W. Ulissi

CoRR, 2020

An Introduction to Electrocatalyst Design using Machine Learning for Renewable Energy Storage.

C. Lawrence Zitnick, Lowik Chanussot, Abhishek Das, Siddharth Goyal, Javier Heras-Domingo, Caleb Ho, Weihua Hu, Thibaut Lavril, Aini Palizhati, Morgane Riviere, Muhammed Shuaibi, Anuroop Sriram, Kevin Tran, Brandon M. Wood, Junwoong Yoon, Devi Parikh, Zachary W. Ulissi

CoRR, 2020