activity
20122014
most citedConvolutional Neural Associative Memories: Massive Capacity with Noise Tolerance

4 citations · 9 across the 6 of their papers we have counts for

collaborators

6 papers

cs.NE2014★ 4 cited

Convolutional Neural Associative Memories: Massive Capacity with Noise Tolerance

Amin Karbasi, Amir Hesam Salavati, Amin Shokrollahi

The task of a neural associative memory is to retrieve a set of previously memorized patterns from their noisy versions using a network of neurons. An ideal network should have the…

cs.NE2014★ 1 cited

Noise Facilitation in Associative Memories of Exponential Capacity

Amin Karbasi, Amir Hesam Salavati, Amin Shokrollahi +1

Recent advances in associative memory design through structured pattern sets and graph-based inference algorithms have allowed reliable learning and recall of an exponential number…

cs.NE2013★ 2 cited

A Non-Binary Associative Memory with Exponential Pattern Retrieval Capacity and Iterative Learning: Extended Results

Amir Hesam Salavati, K. Raj Kumar, Amin Shokrollahi

We consider the problem of neural association for a network of non-binary neurons. Here, the task is to first memorize a set of patterns using a network of neurons whose states ass…

cs.NE2013

Neural Networks Built from Unreliable Components

Amin Karbasi, Amir Hesam Salavati, Amin Shokrollahi +1

Recent advances in associative memory design through strutured pattern sets and graph-based inference algorithms have allowed the reliable learning and retrieval of an exponential…

cs.NE2013★ 1 cited

Coupled Neural Associative Memories

Amin Karbasi, Amir Hesam Salavati, Amin Shokrollahi

We propose a novel architecture to design a neural associative memory that is capable of learning a large number of patterns and recalling them later in presence of noise. It is ba…

cs.NE2012★ 1 cited

Multi-Level Error-Resilient Neural Networks with Learning

Amir Hesam Salavati, Amin Karbasi

The problem of neural network association is to retrieve a previously memorized pattern from its noisy version using a network of neurons. An ideal neural network should include th…