Explainable Inference on Sequential Data via Memory-Tracking

In this paper we present a novel mechanism to get explanations that allow to better understand network predictions when dealing with sequential data. Specifically, we adopt memory-based networks — Differential Neural Computers — to exploit their capability of storing data in memory and reusing it for inference... (read more)

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METHOD TYPE
Memory Network
Working Memory Models
Content-based Attention
Attention Mechanisms