Gabriel Huang
Gabriel Huang
PhD student, Montreal Institute for Learning Algorithms
Adresse e-mail validée de umontreal.ca - Page d'accueil
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Negative momentum for improved game dynamics
G Gidel, RA Hemmat, M Pezeshki, R Le Priol, G Huang, S Lacoste-Julien, ...
The 22nd International Conference on Artificial Intelligence and Statistics …, 2019
832019
Scattering networks for hybrid representation learning
E Oyallon, S Zagoruyko, G Huang, N Komodakis, S Lacoste-Julien, ...
IEEE transactions on pattern analysis and machine intelligence 41 (9), 2208-2221, 2018
272018
Are Few-Shot Learning Benchmarks too Simple ? Solving them without Test-Time Labels
G Huang, H Larochelle, S Lacoste-Julien
arXiv preprint arXiv:1902.08605, 2019
13*2019
Parametric Adversarial Divergences are Good Task Losses for Generative Modeling
G Huang, H Berard, A Touati, G Gidel, P Vincent, S Lacoste-Julien
arXiv preprint arXiv:1708.02511, 2017
92017
Multimodal Pretraining for Dense Video Captioning
G Huang, B Pang, Z Zhu, C Rivera, R Soricut
arXiv preprint arXiv:2011.11760, 2020
22020
Parametric Adversarial Divergences are Good Task Losses for Generative Modeling. arXiv. org
G Huang, H Berard, A Touati, G Gidel, P Vincent, S Lacoste-Julien
August, 2017
22017
Repurposing Pretrained Models for Robust Out-of-domain Few-Shot Learning
N Kwon, H Na, G Huang, S Lacoste-Julien
arXiv preprint arXiv:2103.09027, 2021
2021
Are Few-Shot Learning Benchmarks too Simple? Solving them without Task Supervision at Test-Time
G Huang, H Larochelle, S Lacoste-Julien
arXiv e-prints, arXiv: 1902.08605, 2019
2019
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