134 citations · 159 across the 2 of their papers we have counts for
3 papers
cs.CV2018
MaskConnect: Connectivity Learning by Gradient Descent
Karim Ahmed, Lorenzo Torresani
Although deep networks have recently emerged as the model of choice for many computer vision problems, in order to yield good results they often require time-consuming architecture…
cs.AI2017★ 134 cited
Weighted Transformer Network for Machine Translation
Karim Ahmed, Nitish Shirish Keskar, Richard Socher
State-of-the-art results on neural machine translation often use attentional sequence-to-sequence models with some form of convolution or recursion. Vaswani et al. (2017) propose a…
cs.LG2017★ 25 cited
Connectivity Learning in Multi-Branch Networks
Karim Ahmed, Lorenzo Torresani
While much of the work in the design of convolutional networks over the last five years has revolved around the empirical investigation of the importance of depth, filter sizes, an…