3.7k citations · 11.8k across the 85 of their papers we have counts for
5 papers · 1 filter
Tracking the World State with Recurrent Entity Networks
Mikael Henaff, Jason Weston, Arthur Szlam +2
We introduce a new model, the Recurrent Entity Network (EntNet). It is equipped with a dynamic long-term memory which allows it to maintain and update a representation of the state…
Geometric deep learning: going beyond Euclidean data
Michael M. Bronstein, Joan Bruna, Yann LeCun +2
Many scientific fields study data with an underlying structure that is a non-Euclidean space. Some examples include social networks in computational social sciences, sensor network…
Learning Multiagent Communication with Backpropagation
Sainbayar Sukhbaatar, Arthur Szlam, Rob Fergus
Many tasks in AI require the collaboration of multiple agents. Typically, the communication protocol between agents is manually specified and not altered during training. In this p…
Accurate principal component analysis via a few iterations of alternating least squares
Arthur Szlam, Andrew Tulloch, Mark Tygert
A few iterations of alternating least squares with a random starting point provably suffice to produce nearly optimal spectral- and Frobenius-norm accuracies of low-rank approximat…
Recurrent Orthogonal Networks and Long-Memory Tasks
Mikael Henaff, Arthur Szlam, Yann LeCun
Although RNNs have been shown to be powerful tools for processing sequential data, finding architectures or optimization strategies that allow them to model very long term dependen…