8 citations · 10 across the 4 of their papers we have counts for
5 papers
Reconstructing a Graph from Path Traces
Vincent Gripon, Michael Rabbat
This paper considers the problem of inferring the structure of a network from indirect observations. Each observation (a "trace") is the unordered set of nodes which are activated…
Maximum Likelihood Associative Memories
Vincent Gripon, Michael Rabbat
Associative memories are structures that store data in such a way that it can later be retrieved given only a part of its content -- a sort-of error/erasure-resilience property. Th…
Learning sparse messages in networks of neural cliques
Behrooz Kamary Aliabadi, Claude Berrou, Vincent Gripon +1
An extension to a recently introduced binary neural network is proposed in order to allow the learning of sparse messages, in large numbers and with high memory efficiency. This ne…
Forwarding Without Repeating: Efficient Rumor Spreading in Bounded-Degree Graphs
Vincent Gripon, Vitaly Skachek, Michael Rabbat
We study a gossip protocol called forwarding without repeating (FWR). The objective is to spread multiple rumors over a graph as efficiently as possible. FWR accomplishes this by h…
Sparse neural networks with large learning diversity
Vincent Gripon, Claude Berrou
Coded recurrent neural networks with three levels of sparsity are introduced. The first level is related to the size of messages, much smaller than the number of available neurons.…