Brandon M. Wood

According to our database, Brandon M. Wood authored at least 19 papers between 2020 and 2026.

Collaborative distances:

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

2026

A recipe for scalable attention-based MLIPs: unlocking long-range accuracy with all-to-all node attention.

Eric Qu, Brandon M. Wood, Aditi S. Krishnapriyan, Zachary W. Ulissi

CoRR, March, 2026

2025

Enhancing Diffusion-Based Sampling with Molecular Collective Variables.

Juno Nam, Bálint Máté, Artur P. Toshev, Manasa Kaniselvan, Rafael Gómez-Bombarelli, Ricky T. Q. Chen, Brandon M. Wood, Guan-Horng Liu, Benjamin Kurt Miller

CoRR, October, 2025

UMA: A Family of Universal Models for Atoms.

Brandon M. Wood, Misko Dzamba, Xiang Fu, Meng Gao, Muhammed Shuaibi, Luis Barroso-Luque, Kareem Abdelmaqsoud, Vahe Gharakhanyan, John R. Kitchin, Daniel S. Levine, Kyle Michel, Anuroop Sriram, Taco Cohen, Abhishek Das, Ammar Rizvi, Sushree Jagriti Sahoo, Zachary W. Ulissi, C. Lawrence Zitnick

CoRR, June, 2025

Adjoint Sampling: Highly Scalable Diffusion Samplers via Adjoint Matching.

Aaron J. Havens, Benjamin Kurt Miller, Bing Yan, Carles Domingo-Enrich, Anuroop Sriram, Brandon M. Wood, Daniel Levine, Bin Hu, Brandon Amos, Brian Karrer, Xiang Fu, Guan-Horng Liu, Ricky T. Q. Chen

CoRR, April, 2025

A practical guide to machine learning interatomic potentials - Status and future.

Ryan Jacobs, Dane Morgan, Siamak Attarian, Jun Meng, Chen Shen, Zhenghao Wu, Clare Yijia Xie, Julia H. Yang, Nongnuch Artrith, Ben Blaiszik, Gerbrand Ceder, Kamal Choudhary, Gábor Csányi, Ekin Dogus Cubuk, Bowen Deng, Ralf Drautz, Xiang Fu, Jonathan Godwin, Vasant G. Honavar, Olexandr Isayev, Anders Johansson, Boris Kozinsky, Stefano Martiniani, Shyue Ping Ong, Igor Poltavsky, K. J. Schmidt, So Takamoto, Aidan Thompson, Julia Westermayr, Brandon M. Wood

CoRR, March, 2025

Adjoint Sampling: Highly Scalable Diffusion Samplers via Adjoint Matching.

Aaron J. Havens, Benjamin Kurt Miller, Bing Yan, Carles Domingo-Enrich, Anuroop Sriram, Daniel S. Levine, Brandon M. Wood, Bin Hu, Brandon Amos, Brian Karrer, Xiang Fu, Guan-Horng Liu, Ricky T. Q. Chen

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Learning Smooth and Expressive Interatomic Potentials for Physical Property Prediction.

Xiang Fu, Brandon M. Wood, Luis Barroso-Luque, Daniel S. Levine, Meng Gao, Misko Dzamba, C. Lawrence Zitnick

Proceedings of the Forty-second International Conference on Machine Learning, 2025

2024

Open Materials 2024 (OMat24) Inorganic Materials Dataset and Models.

Luis Barroso-Luque, Muhammed Shuaibi, Xiang Fu, Brandon M. Wood, Misko Dzamba, Meng Gao, Ammar Rizvi, C. Lawrence Zitnick, Zachary W. Ulissi

CoRR, 2024

FlowLLM: Flow Matching for Material Generation with Large Language Models as Base Distributions.

Anuroop Sriram, Benjamin Kurt Miller, Ricky T. Q. Chen, Brandon M. Wood

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

FlowMM: Generating Materials with Riemannian Flow Matching.

Benjamin Kurt Miller, Ricky T. Q. Chen, Anuroop Sriram, Brandon M. Wood

Proceedings of the Forty-first International Conference on Machine Learning, 2024

From Molecules to Materials: Pre-training Large Generalizable Models for Atomic Property Prediction.

Nima Shoghi, Adeesh Kolluru, John R. Kitchin, Zachary W. Ulissi, C. Lawrence Zitnick, Brandon M. Wood

Proceedings of the Twelfth International Conference on Learning Representations, 2024

EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations.

Yi-Lun Liao, Brandon M. Wood, Abhishek Das, Tess E. Smidt

Proceedings of the Twelfth International Conference on Learning Representations, 2024

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

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

Towards Training Billion Parameter Graph Neural Networks for Atomic Simulations.

Anuroop Sriram, Abhishek Das, Brandon M. Wood, Siddharth Goyal, C. Lawrence Zitnick

Proceedings of the Tenth International Conference on Learning Representations, 2022

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