Wood, Brandon M

9 publications

ICML 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

ICLRW 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

ICML 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

NeurIPS 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, Sushree Jagriti Sahoo, Ammar Rizvi, Zachary Ward Ulissi, C. Lawrence Zitnick

ICLR 2024 EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations Yi-Lun Liao, Brandon M Wood, Abhishek Das, Tess Smidt

NeurIPS 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

ICML 2024 FlowMM: Generating Materials with Riemannian Flow Matching Benjamin Kurt Miller, Ricky T. Q. Chen, Anuroop Sriram, Brandon M Wood

ICLR 2024 From Molecules to Materials: Pre-Training Large Generalizable Models for Atomic Property Prediction Nima Shoghi, Adeesh Kolluru, John R. Kitchin, Zachary Ward Ulissi, C. Lawrence Zitnick, Brandon M Wood

ICLR 2022 Towards Training Billion Parameter Graph Neural Networks for Atomic Simulations Anuroop Sriram, Abhishek Das, Brandon M Wood, Siddharth Goyal, C. Lawrence Zitnick