Matthew Le
Matthew Le
Facebook AI Research
Vahvistettu sähköpostiosoite verkkotunnuksessa
Flow matching for generative modeling
Y Lipman, RTQ Chen, H Ben-Hamu, M Nickel, M Le
arXiv preprint arXiv:2210.02747, 2022
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
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
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
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
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
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
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
Learning multivariate Hawkes processes at scale
M Nickel, M Le
arXiv preprint arXiv:2002.12501, 2020
Partial aborts for transactions via first-class continuations
M Le, M Fluet
ACM SIGPLAN Notices 50 (9), 230-242, 2015
Practical and effective higher-order optimizations
L Bergstrom, M Fluet, M Le, J Reppy, N Sandler
ACM SIGPLAN Notices 49 (9), 81-93, 2014
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
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
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
Revisiting software transactional memory in Haskell
M Le, R Yates, M Fluet
ACM SIGPLAN Notices 51 (12), 105-113, 2016
Flow matching for generative modeling, 2022
Y Lipman, RTQ Chen, H Ben-Hamu, M Nickel, M Le
URL https://arxiv. org/abs/2210.02747, 0
A compiler extension for parallel matrix programming
K Williams, M Le, T Kaminski, E Van Wyk
2014 43rd International Conference on Parallel Processing, 471-480, 2014
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Artikkelit 1–20