Brandon M. Wood

26 papers A* 8Journal 17Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A recipe for scalable attention-based MLIPs: unlocking long-range accuracy with all-to-all node attention. CoRR Eric Qu, Brandon M. Wood, Aditi S. Krishnapriyan, Zachary W. Ulissi
2025	J	`jnl`	A practical guide to machine learning interatomic potentials - Status and future. CoRR 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
2025	A*	`conf`	Adjoint Sampling: Highly Scalable Diffusion Samplers via Adjoint Matching. ICML 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
2025	J	`jnl`	Adjoint Sampling: Highly Scalable Diffusion Samplers via Adjoint Matching. CoRR 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
2025	J	`jnl`	Enhancing Diffusion-Based Sampling with Molecular Collective Variables. CoRR 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
2025	A*	`conf`	Learning Smooth and Expressive Interatomic Potentials for Physical Property Prediction. ICML Xiang Fu, Brandon M. Wood, Luis Barroso-Luque, Daniel S. Levine, Meng Gao, Misko Dzamba, C. Lawrence Zitnick
2025	J	`jnl`	Learning Smooth and Expressive Interatomic Potentials for Physical Property Prediction. CoRR Xiang Fu, Brandon M. Wood, Luis Barroso-Luque, Daniel S. Levine, Meng Gao, Misko Dzamba, C. Lawrence Zitnick
2025	J	`jnl`	UMA: A Family of Universal Models for Atoms. CoRR 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
2024	A*	`conf`	EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations. ICLR Yi-Lun Liao, Brandon M. Wood, Abhishek Das, Tess E. Smidt
2024	A*	`conf`	FlowLLM: Flow Matching for Material Generation with Large Language Models as Base Distributions. NeurIPS Anuroop Sriram, Benjamin Kurt Miller, Ricky T. Q. Chen, Brandon M. Wood
2024	J	`jnl`	FlowLLM: Flow Matching for Material Generation with Large Language Models as Base Distributions. CoRR Anuroop Sriram, Benjamin Kurt Miller, Ricky T. Q. Chen, Brandon M. Wood
2024	A*	`conf`	FlowMM: Generating Materials with Riemannian Flow Matching. ICML Benjamin Kurt Miller, Ricky T. Q. Chen, Anuroop Sriram, Brandon M. Wood
2024	J	`jnl`	FlowMM: Generating Materials with Riemannian Flow Matching. CoRR Benjamin Kurt Miller, Ricky T. Q. Chen, Anuroop Sriram, Brandon M. Wood
2024	A*	`conf`	From Molecules to Materials: Pre-training Large Generalizable Models for Atomic Property Prediction. ICLR Nima Shoghi, Adeesh Kolluru, John R. Kitchin, Zachary W. Ulissi, C. Lawrence Zitnick, Brandon M. Wood
2024	J	`jnl`	Open Materials 2024 (OMat24) Inorganic Materials Dataset and Models. CoRR Luis Barroso-Luque, Muhammed Shuaibi, Xiang Fu, Brandon M. Wood, Misko Dzamba, Meng Gao, Ammar Rizvi, C. Lawrence Zitnick, Zachary W. Ulissi
2023	J	`jnl`	EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations. CoRR Yi-Lun Liao, Brandon M. Wood, Abhishek Das, Tess E. Smidt
2023	J	`jnl`	From Molecules to Materials: Pre-training Large Generalizable Models for Atomic Property Prediction. CoRR Nima Shoghi, Adeesh Kolluru, John R. Kitchin, Zachary W. Ulissi, C. Lawrence Zitnick, Brandon M. Wood
2022	J	`jnl`	AdsorbML: Accelerating Adsorption Energy Calculations with Machine Learning. CoRR Janice Lan, Aini Palizhati, Muhammed Shuaibi, Brandon M. Wood, Brook Wander, Abhishek Das, Matt Uyttendaele, C. Lawrence Zitnick, Zachary W. Ulissi
2022	A*	`conf`	Spherical Channels for Modeling Atomic Interactions. NeurIPS Larry Zitnick, Abhishek Das, Adeesh Kolluru, Janice Lan, Muhammed Shuaibi, Anuroop Sriram, Zachary W. Ulissi, Brandon M. Wood
2022	J	`jnl`	Spherical Channels for Modeling Atomic Interactions. CoRR C. Lawrence Zitnick, Abhishek Das, Adeesh Kolluru, Janice Lan, Muhammed Shuaibi, Anuroop Sriram, Zachary W. Ulissi, Brandon M. Wood
2022	J	`jnl`	The Open Catalyst 2022 (OC22) Dataset and Challenges for Oxide Electrocatalysis. CoRR 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
2022	A*	`conf`	Towards Training Billion Parameter Graph Neural Networks for Atomic Simulations. ICLR Anuroop Sriram, Abhishek Das, Brandon M. Wood, Siddharth Goyal, C. Lawrence Zitnick
2022	J	`jnl`	Towards Training Billion Parameter Graph Neural Networks for Atomic Simulations. CoRR Anuroop Sriram, Abhishek Das, Brandon M. Wood, Siddharth Goyal, C. Lawrence Zitnick
2021	—	`conf`	The Open Catalyst Challenge 2021: Competition Report. NeurIPS (Competition and Demos) 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
2020	J	`jnl`	An Introduction to Electrocatalyst Design using Machine Learning for Renewable Energy Storage. CoRR 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
2020	J	`jnl`	The Open Catalyst 2020 (OC20) Dataset and Community Challenges. CoRR 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