Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Lopes, Raphael Gontijo"'
Autor:
Dohan, David, Xu, Winnie, Lewkowycz, Aitor, Austin, Jacob, Bieber, David, Lopes, Raphael Gontijo, Wu, Yuhuai, Michalewski, Henryk, Saurous, Rif A., Sohl-dickstein, Jascha, Murphy, Kevin, Sutton, Charles
Prompted models have demonstrated impressive few-shot learning abilities. Repeated interactions at test-time with a single model, or the composition of multiple models together, further expands capabilities. These compositions are probabilistic model
Externí odkaz:
http://arxiv.org/abs/2207.10342
Autor:
Chen, Liang-Chieh, Lopes, Raphael Gontijo, Cheng, Bowen, Collins, Maxwell D., Cubuk, Ekin D., Zoph, Barret, Adam, Hartwig, Shlens, Jonathon
Supervised learning in large discriminative models is a mainstay for modern computer vision. Such an approach necessitates investing in large-scale human-annotated datasets for achieving state-of-the-art results. In turn, the efficacy of supervised l
Externí odkaz:
http://arxiv.org/abs/2005.10266
Achieving robustness to distributional shift is a longstanding and challenging goal of computer vision. Data augmentation is a commonly used approach for improving robustness, however robustness gains are typically not uniform across corruption types
Externí odkaz:
http://arxiv.org/abs/1906.08988
Deploying machine learning systems in the real world requires both high accuracy on clean data and robustness to naturally occurring corruptions. While architectural advances have led to improved accuracy, building robust models remains challenging.
Externí odkaz:
http://arxiv.org/abs/1906.02611
Dramatic advances in generative models have resulted in near photographic quality for artificially rendered faces, animals and other objects in the natural world. In spite of such advances, a higher level understanding of vision and imagery does not
Externí odkaz:
http://arxiv.org/abs/1904.02632
Autor:
Hori, Chiori, Alamri, Huda, Wang, Jue, Wichern, Gordon, Hori, Takaaki, Cherian, Anoop, Marks, Tim K., Cartillier, Vincent, Lopes, Raphael Gontijo, Das, Abhishek, Essa, Irfan, Batra, Dhruv, Parikh, Devi
Dialog systems need to understand dynamic visual scenes in order to have conversations with users about the objects and events around them. Scene-aware dialog systems for real-world applications could be developed by integrating state-of-the-art tech
Externí odkaz:
http://arxiv.org/abs/1806.08409
Autor:
Alamri, Huda, Cartillier, Vincent, Lopes, Raphael Gontijo, Das, Abhishek, Wang, Jue, Essa, Irfan, Batra, Dhruv, Parikh, Devi, Cherian, Anoop, Marks, Tim K., Hori, Chiori
Scene-aware dialog systems will be able to have conversations with users about the objects and events around them. Progress on such systems can be made by integrating state-of-the-art technologies from multiple research areas including end-to-end dia
Externí odkaz:
http://arxiv.org/abs/1806.00525
Recent advances in model compression have provided procedures for compressing large neural networks to a fraction of their original size while retaining most if not all of their accuracy. However, all of these approaches rely on access to the origina
Externí odkaz:
http://arxiv.org/abs/1710.07535