Gabriel Huang

According to our database, Gabriel Huang authored at least 9 papers between 2017 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

A Survey of Self-Supervised and Few-Shot Object Detection.

Gabriel Huang, Issam H. Laradji, David Vázquez, Simon Lacoste-Julien, Pau Rodríguez

IEEE Trans. Pattern Anal. Mach. Intell., April, 2023

GEO-Bench: Toward Foundation Models for Earth Monitoring.

Alexandre Lacoste, Nils Lehmann, Pau Rodríguez, Evan D. Sherwin, Hannah Kerner, Björn Lütjens, Jeremy Irvin, David Dao, Hamed Alemohammad, Alexandre Drouin, Mehmet Gunturkun, Gabriel Huang, David Vázquez, Dava Newman, Yoshua Bengio, Stefano Ermon, Xiaoxiang Zhu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2021

Repurposing Pretrained Models for Robust Out-of-domain Few-Shot Learning.

Namyeong Kwon, Hwidong Na, Gabriel Huang, Simon Lacoste-Julien

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Multimodal Pretraining for Dense Video Captioning.

Gabriel Huang, Bo Pang, Zhenhai Zhu, Clara Rivera, Radu Soricut

Proceedings of the 1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 10th International Joint Conference on Natural Language Processing, 2020

2019

Scattering Networks for Hybrid Representation Learning.

Edouard Oyallon, Sergey Zagoruyko, Gabriel Huang, Nikos Komodakis, Simon Lacoste-Julien, Matthew B. Blaschko, Eugene Belilovsky

IEEE Trans. Pattern Anal. Mach. Intell., 2019

Centroid Networks for Few-Shot Clustering and Unsupervised Few-Shot Classification.

Gabriel Huang, Hugo Larochelle, Simon Lacoste-Julien

CoRR, 2019

Negative Momentum for Improved Game Dynamics.

Gauthier Gidel, Reyhane Askari Hemmat, Mohammad Pezeshki, Rémi Le Priol, Gabriel Huang, Simon Lacoste-Julien, Ioannis Mitliagkas

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Parametric Adversarial Divergences are Good Task Losses for Generative Modeling.

Gabriel Huang, Hugo Berard, Ahmed Touati, Gauthier Gidel, Pascal Vincent, Simon Lacoste-Julien

Proceedings of the 6th International Conference on Learning Representations, 2018

2017

Adversarial Divergences are Good Task Losses for Generative Modeling.

Gabriel Huang, Gauthier Gidel, Hugo Berard, Ahmed Touati, Simon Lacoste-Julien

CoRR, 2017