Xiang Fu

1. The Open Molecules 2025 (OMol25) Dataset, Evaluations, and Models
   2025/05/13 by Daniel S. Levine, Muhammed Shuaibi, Levine, Daniel S. +43 · 6 voices · 29 citations
   #physics.chem-ph
2. Crystal Diffusion Variational Autoencoder for Periodic Material Generation
   2021/10/12 by Tian Xie, Xie, Tian, Xiang Fu +7 · 61 citations
   Materials Science · Engineering · #Machine Learning in Materials Science #X-ray Diffraction in Crystallography #Surface Chemistry and Catalysis
3. MatterGen: a generative model for inorganic materials design
   2023/12/06 by Claudio Zeni, Zeni, Claudio, Robert Pinsler +41 · 1 voice · 25 citations
   Computer Science · Engineering · Materials Science · Physics and Astronomy · #Machine Learning in Materials Science #Modular Robots and Swarm Intelligence #cond-mat.mtrl-sci #cs.AI
4. Open Materials 2024 (OMat24) Inorganic Materials Dataset and Models
   2024/10/16 by Luis Barroso-Luque, Muhammed Shuaibi, Barroso-Luque, Luis +15 · 49 citations
   Materials Science · #Machine Learning in Materials Science
5. Learning Smooth and Expressive Interatomic Potentials for Physical Property Prediction
   2025/02/17 by Xiang Fu, Fu, Xiang, Brandon M. Wood +11 · 1 voice · 56 citations
   Computer Science · Engineering · #Hand Gesture Recognition Systems #Robot Manipulation and Learning #Software Engineering Research #cs.LG #physics.comp-ph
6. Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems
   2023/07/17 by Xuan Zhang, Zhang, Xuan, Limei Wang +123 · 1 voice · 22 citations
   #cs.LG #physics.comp-ph
7. Forces are not Enough: Benchmark and Critical Evaluation for Machine Learning Force Fields with Molecular Simulations
   2022/10/13 by Xiang Fu, Zhenghao Wu, Wujie Wang +4 · 1 voice · 12 citations
   Physics and Astronomy · Computer Science · #physics.comp-ph #cs.LG #physics.chem-ph
8. Adjoint Sampling: Highly Scalable Diffusion Samplers via Adjoint Matching
   2025/04/16 by Aaron Havens, Aaron M. Havens, Benjamin Kurt Miller +26 · 2 voices · 31 citations
   Materials Science · Computer Science · #Machine Learning in Materials Science #Advanced Graph Neural Networks #Gaussian Processes and Bayesian Inference
9. UMA: A Family of Universal Models for Atoms
   2025/06/30 by Brandon M. Wood, Wood, Brandon M., Misko Dzamba +33 · 50 citations
   Materials Science · Decision Sciences · Chemical Engineering · #Machine Learning in Materials Science #Scientific Computing and Data Management #Catalysis and Oxidation Reactions
10. All-atom Diffusion Transformers: Unified generative modelling of molecules and materials
    2025/03/05 by Chaitanya K. Joshi, Joshi, Chaitanya K., Xiang Fu +11 · 32 citations
    Materials Science · Physics and Astronomy · #Machine Learning in Materials Science #Block Copolymer Self-Assembly #Quantum many-body systems
11. Randomised benchmarking for characterizing and forecasting correlated processes
    2023/12/11 by Xinfang Zhang, Zhang, Xinfang, Zhihao Wu +27 · 7 citations
    Computer Science · Physics and Astronomy · #FOS: Physical sciences #Neural Networks and Applications #Quantum Computing Algorithms and Architecture #Quantum Physics (quant-ph) #Quantum many-body systems
12. M²IV: Towards Efficient and Fine-grained Multimodal In-Context Learning via Representation Engineering
    2025/04/06 by Yanshu Li, Li, Yanshu, Yi Cao +13 · 17 citations
    Computer Science · #Human Pose and Action Recognition
13. Virtual Node Graph Neural Network for Full Phonon Prediction
    2023/01/05 by Ryotaro Okabe, Abhijatmedhi Chotrattanapituk, Okabe, Ryotaro +23 · 4 citations
    Materials Science · #Computational Physics (physics.comp-ph) #Disordered Systems and Neural Networks (cond-mat.dis-nn) #FOS: Physical sciences #Machine Learning in Materials Science #X-ray Diffraction in Crystallography
14. A Recipe for Charge Density Prediction
    2024/05/29 by Xiang Fu, Andrew Rosen, Fu, Xiang +13 · 6 citations
    Materials Science · #Computational Physics (physics.comp-ph) #Electron and X-Ray Spectroscopy Techniques #FOS: Computer and information sciences #FOS: Physical sciences #Machine Learning (cs.LG)
15. Learning to See Physical Properties with Active Sensing Motor Policies
    2023/11/02 by Gabriel B. Margolis, Margolis, Gabriel B., Xiang Fu +5 · 4 citations
    Engineering · Computer Science · #Robotic Locomotion and Control #Robot Manipulation and Learning #Anomaly Detection Techniques and Applications
16. Fragment-based Sequential Translation for Molecular Optimization
    2021/10/26 by Benson Chen, Chen, Benson, Xiang Fu +5 · 1 citation
    Computer Science · Materials Science · Engineering · #Computational Drug Discovery Methods #Machine Learning in Materials Science #Innovative Microfluidic and Catalytic Techniques Innovation
17. Towards a Theory of Web Service Choreographies
    2008/04/12 by Jianwen Su, Tevfik Bultan, Xiang Fu +1 · 1 citation
    Business, Management and Accounting · Computer Science · #Advanced Software Engineering Methodologies #Business Process Modeling and Analysis #Service-Oriented Architecture and Web Services
18. An overview of research on waverider design methodology
    2017/08/25 by Feng Ding, Jun Liu, Chibing Shen +4 · 1 citation
    Engineering · Mathematics · #Computational Fluid Dynamics and Aerodynamics #Plasma and Flow Control in Aerodynamics #Gas Dynamics and Kinetic Theory