Muhammed Shuaibi

发表

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

C. Lawrence Zitnick, Aini Palizhati, Zachary W. Ulissi, 2020, ArXiv.

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

C. Lawrence Zitnick, Aini Palizhati, Kevin Tran, 2020, Proceedings of the International Conference on Electrocatalysis for Energy Applications and Sustainable Chemicals.

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

Zachary W. Ulissi, Brandon M. Wood, C. L. Zitnick, 2022, ArXiv.

Open Challenges in Developing Generalizable Large-Scale Machine-Learning Models for Catalyst Discovery

Zachary W. Ulissi, C. L. Zitnick, Abhishek Das, 2022, ACS Catalysis.

Spherical Channels for Modeling Atomic Interactions

Zachary W. Ulissi, C. L. Zitnick, Janice Lan, 2022, ArXiv.

Correction to “The Open Catalyst 2020 (OC20) Dataset and Community Challenges”

Zachary W. Ulissi, C. L. Zitnick, Anuroop Sriram, 2021, ACS Catalysis.

Transfer learning using attentions across atomic systems with graph neural networks (TAAG).

Zachary W. Ulissi, C. L. Zitnick, Siddharth Goyal, 2022, The Journal of chemical physics.

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

Zachary W. Ulissi, Brandon M. Wood, C. L. Zitnick, 2022, ArXiv.

The Open Catalyst 2020 (OC20) Dataset and Community Challenges

Weihua Hu, C. Lawrence Zitnick, Aini Palizhati, 2020, ACS Catalysis.

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

Zachary W. Ulissi, Brandon M. Wood, C. L. Zitnick, 2022, ArXiv.

AdsorbML: Accelerating Adsorption Energy Calculations with Machine Learning

Zachary W. Ulissi, Brandon M. Wood, C. L. Zitnick, 2022, ArXiv.

AdsorbML: Accelerating Adsorption Energy Calculations with Machine Learning

Zachary W. Ulissi, Brandon M. Wood, C. L. Zitnick, 2022, ArXiv.

Open Catalyst 2020 (OC20) Dataset and Community Challenges

Zachary W. Ulissi, C. L. Zitnick, Anuroop Sriram, 2020, ACS Catalysis.

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

Zachary W. Ulissi, Muhammed Shuaibi, Saurabh Sivakumar, 2020, Mach. Learn. Sci. Technol..

GemNet-OC: Developing Graph Neural Networks for Large and Diverse Molecular Simulation Datasets

Zachary W. Ulissi, C. L. Zitnick, J. Gasteiger, 2022, Trans. Mach. Learn. Res..

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

Zachary W. Ulissi, Brandon M. Wood, C. L. Zitnick, 2022, ACS Catalysis.

Spherical Channels for Modeling Atomic Interactions

Zachary W. Ulissi, C. L. Zitnick, Janice Lan, 2022, NeurIPS.

Rotation Invariant Graph Neural Networks using Spin Convolutions pdf

C. Lawrence Zitnick, Zachary W. Ulissi, Anuroop Sriram, 2021, ArXiv.

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

J. Leskovec, C. L. Zitnick, Anuroop Sriram, 2021, ArXiv.

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

Zachary W. Ulissi, C. L. Zitnick, Anuroop Sriram, 2022, ArXiv.

The Open Catalyst Challenge 2021: Competition Report

Zachary W. Ulissi, C. L. Zitnick, Janice Lan, 2021, Neural Information Processing Systems.

AdsorbML: a leap in efficiency for adsorption energy calculations using generalizable machine learning potentials

Zachary W. Ulissi, Brandon M. Wood, C. L. Zitnick, 2022, npj Computational Materials.

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

Jure Leskovec, Weihua Hu, C. Lawrence Zitnick, 2021, ArXiv.

Chemical Properties from Graph Neural Network-Predicted Electron Densities

Zachary W. Ulissi, Muhammed Shuaibi, John R. Kitchin, 2023, The Journal of Physical Chemistry C.

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

Zachary W. Ulissi, Benjamin M. Comer, Muhammed Shuaibi, 2023, J. Open Source Softw..