Matthew Le
Matthew Le
Facebook AI Research
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Flow matching for generative modeling
Y Lipman, RTQ Chen, H Ben-Hamu, M Nickel, M Le
arXiv preprint arXiv:2210.02747, 2022
Voicebox: Text-guided multilingual universal speech generation at scale
M Le, A Vyas, B Shi, B Karrer, L Sari, R Moritz, M Williamson, V Manohar, ...
Advances in neural information processing systems 36, 2024
Inferring concept hierarchies from text corpora via hyperbolic embeddings
M Le, S Roller, L Papaxanthos, D Kiela, M Nickel
arXiv preprint arXiv:1902.00913, 2019
Revisiting the evaluation of theory of mind through question answering
M Le, YL Boureau, M Nickel
Proceedings of the 2019 Conference on Empirical Methods in Natural Language …, 2019
A parameter-free spatio-temporal pattern mining model to catalog global ocean dynamics
JH Faghmous, M Le, M Uluyol, V Kumar, S Chatterjee
2013 IEEE 13th International conference on data mining, 151-160, 2013
Audiobox: Unified audio generation with natural language prompts
A Vyas, B Shi, M Le, A Tjandra, YC Wu, B Guo, J Zhang, X Zhang, ...
arXiv preprint arXiv:2312.15821, 2023
Assessment of risk of harm associated with intensive blood pressure management among patients with hypertension who smoke: a secondary analysis of the systolic blood pressure …
J Scarpa, E Bruzelius, P Doupe, M Le, J Faghmous, A Baum
JAMA network open 2 (3), e190005-e190005, 2019
Facebook AI's WAT19 Myanmar-English translation task submission
PJ Chen, J Shen, M Le, V Chaudhary, A El-Kishky, G Wenzek, M Ott, ...
arXiv preprint arXiv:1910.06848, 2019
Satellite images and machine learning can identify remote communities to facilitate access to health services
E Bruzelius, M Le, A Kenny, J Downey, M Danieletto, A Baum, P Doupe, ...
Journal of the American Medical Informatics Association 26 (8-9), 806-812, 2019
The source-target domain mismatch problem in machine translation
J Shen, PJ Chen, M Le, J He, J Gu, M Ott, M Auli, MA Ranzato
arXiv preprint arXiv:1909.13151, 2019
Multiple hypothesis object tracking for unsupervised self-learning: An ocean eddy tracking application
J Faghmous, M Uluyol, L Styles, M Le, V Mithal, S Boriah, V Kumar
Proceedings of the AAAI Conference on Artificial Intelligence 27 (1), 1277-1283, 2013
Learning multivariate Hawkes processes at scale
M Nickel, M Le
arXiv preprint arXiv:2002.12501, 2020
On kinetic optimal probability paths for generative models
N Shaul, RTQ Chen, M Nickel, M Le, Y Lipman
International Conference on Machine Learning, 30883-30907, 2023
Partial aborts for transactions via first-class continuations
M Le, M Fluet
ACM SIGPLAN Notices 50 (9), 230-242, 2015
Guided flows for generative modeling and decision making
Q Zheng, M Le, N Shaul, Y Lipman, A Grover, RTQ Chen
arXiv preprint arXiv:2311.13443, 2023
Generative pre-training for speech with flow matching
AH Liu, M Le, A Vyas, B Shi, A Tjandra, WN Hsu
arXiv preprint arXiv:2310.16338, 2023
Modeling sparse information diffusion at scale via lazy multivariate hawkes processes
M Nickel, M Le
Proceedings of the Web Conference 2021, 706-717, 2021
Neural relational autoregression for high-resolution COVID-19 forecasting
M Le, M Ibrahim, L Sagun, T Lacroix, M Nickel
Facebook AI Research, 2020
Practical and effective higher-order optimizations
L Bergstrom, M Fluet, M Le, J Reppy, N Sandler
ACM SIGPLAN Notices 49 (9), 81-93, 2014
Spatio-temporal consistency as a means to identify unlabeled objects in a continuous data field
J Faghmous, H Nguyen, M Le, V Kumar
Proceedings of the AAAI Conference on Artificial Intelligence 28 (1), 2014
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Artículos 1–20