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Xiang Fu
Xiang Fu
FAIR at Meta
Email verificata su meta.com - Home page
Titolo
Citata da
Citata da
Anno
Crystal diffusion variational autoencoder for periodic material generation
T Xie, X Fu, OE Ganea, R Barzilay, T Jaakkola
The Tenth International Conference on Learning Representations (ICLR), 2021
2642021
Forces are not enough: Benchmark and critical evaluation for machine learning force fields with molecular simulations
X Fu, Z Wu, W Wang, T Xie, S Keten, R Gomez-Bombarelli, T Jaakkola
Transactions on Machine Learning Research (TMLR), 2022
1942022
Artificial intelligence for science in quantum, atomistic, and continuum systems
X Zhang, L Wang, J Helwig, Y Luo, C Fu, Y Xie, M Liu, Y Lin, Z Xu, K Yan, ...
arXiv preprint arXiv:2307.08423, 2023
1182023
A generative model for inorganic materials design
C Zeni, R Pinsler, D Zügner, A Fowler, M Horton, X Fu, Z Wang, ...
Nature, 1-3, 2025
106*2025
Learning to Jump from Pixels
GB Margolis, T Chen, K Paigwar, X Fu, D Kim, S bae Kim, P Agrawal
5th Annual Conference on Robot Learning (CoRL), 2021
912021
Learning Task Informed Abstractions
X Fu, G Yang, P Agrawal, T Jaakkola
International Conference on Machine Learning (ICML), 3480-3491, 2021
732021
Simulate time-integrated coarse-grained molecular dynamics with multi-scale graph networks
X Fu, T Xie, NJ Rebello, BD Olsen, T Jaakkola
Transactions on Machine Learning Research (TMLR), 2022
41*2022
The impact of large language models on scientific discovery: a preliminary study using gpt-4
MR AI4Science, MA Quantum
arXiv preprint arXiv:2311.07361, 2023
382023
Mofdiff: Coarse-grained diffusion for metal-organic framework design
X Fu, T Xie, AS Rosen, T Jaakkola, J Smith
The Twelfth International Conference on Learning Representations (ICLR), 2023
172023
Modelling and analysis of tagging networks in Stack Exchange Communities
X Fu, S Yu, AR Benson
Journal of Complex Networks 8 (5), cnz045, 2020
142020
Learning to See Physical Properties with Active Sensing Motor Policies
GB Margolis, X Fu, Y Ji, P Agrawal
Conference on Robot Learning (CoRL), 2023
132023
Open materials 2024 (omat24) inorganic materials dataset and models
L Barroso-Luque, M Shuaibi, X Fu, BM Wood, M Dzamba, M Gao, A Rizvi, ...
arXiv preprint arXiv:2410.12771, 2024
102024
Fragment-based sequential translation for molecular optimization
B Chen, X Fu, R Barzilay, T Jaakkola
arXiv preprint arXiv:2111.01009, 2021
92021
Virtual node graph neural network for full phonon prediction
R Okabe, A Chotrattanapituk, A Boonkird, N Andrejevic, X Fu, ...
Nature Computational Science 4 (7), 522-531, 2024
82024
Thermodynamically Informed Multimodal Learning of High-Dimensional Free Energy Models in Molecular Coarse Graining
BR Duschatko, X Fu, C Owen, Y Xie, A Musaelian, T Jaakkola, B Kozinsky
arXiv preprint arXiv:2405.19386, 2024
52024
Learning Interatomic Potentials at Multiple Scales
X Fu, A Musaelian, A Johansson, T Jaakkola, B Kozinsky
NeurIPS 2023 AI for Materials Workshop, 2023
22023
Structural constraint integration in generative model for discovery of quantum material candidates
R Okabe, M Cheng, A Chotrattanapituk, NT Hung, X Fu, B Han, Y Wang, ...
arXiv preprint arXiv:2407.04557, 2024
12024
Latent Space Simulator for Unveiling Molecular Free Energy Landscapes and Predicting Transition Dynamics
S Dobers, H Stark, X Fu, D Beaini, S Günnemann
NeurIPS 2023 AI for Science Workshop, 2023
12023
A Recipe for Charge Density Prediction
X Fu, A Rosen, K Bystrom, R Wang, A Musaelian, B Kozinsky, T Smidt, ...
arXiv preprint arXiv:2405.19276, 2024
2024
Il sistema al momento non può eseguire l'operazione. Riprova più tardi.
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