5.7k citations · 17.6k across the 75 of their papers we have counts for
9 papers · 1 filter
GuessWhat?! Visual object discovery through multi-modal dialogue
Harm de Vries, Florian Strub, Sarath Chandar +3
We introduce GuessWhat?!, a two-player guessing game as a testbed for research on the interplay of computer vision and dialogue systems. The goal of the game is to locate an unknow…
Deep Learning with Coherent Nanophotonic Circuits
Yichen Shen, Nicholas C. Harris, Scott Skirlo +8
Artificial Neural Networks are computational network models inspired by signal processing in the brain. These models have dramatically improved the performance of many learning tas…
Deep learning trends for focal brain pathology segmentation in MRI
Mohammad Havaei, Nicolas Guizard, Hugo Larochelle +1
Segmentation of focal (localized) brain pathologies such as brain tumors and brain lesions caused by multiple sclerosis and ischemic strokes are necessary for medical diagnosis, su…
Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations
David Krueger, Tegan Maharaj, János Kramár +7
We propose zoneout, a novel method for regularizing RNNs. At each timestep, zoneout stochastically forces some hidden units to maintain their previous values. Like dropout, zoneout…
Neural Autoregressive Distribution Estimation
Benigno Uria, Marc-Alexandre Côté, Karol Gregor +2
We present Neural Autoregressive Distribution Estimation (NADE) models, which are neural network architectures applied to the problem of unsupervised distribution and density estim…
Hierarchical Memory Networks
Sarath Chandar, Sungjin Ahn, Hugo Larochelle +3
Memory networks are neural networks with an explicit memory component that can be both read and written to by the network. The memory is often addressed in a soft way using a softm…
Movie Description
Anna Rohrbach, Atousa Torabi, Marcus Rohrbach +5
Audio Description (AD) provides linguistic descriptions of movies and allows visually impaired people to follow a movie along with their peers. Such descriptions are by design main…
Document Neural Autoregressive Distribution Estimation
Stanislas Lauly, Yin Zheng, Alexandre Allauzen +1
We present an approach based on feed-forward neural networks for learning the distribution of textual documents. This approach is inspired by the Neural Autoregressive Distribution…
Recurrent Mixture Density Network for Spatiotemporal Visual Attention
Loris Bazzani, Hugo Larochelle, Lorenzo Torresani
In many computer vision tasks, the relevant information to solve the problem at hand is mixed to irrelevant, distracting information. This has motivated researchers to design atten…