The DEformer: An Order-Agnostic Distribution Estimating Transformer

Published: Jun 13, 2021
Abstract
Order-agnostic autoregressive distribution estimation (OADE), i.e., autoregressive distribution estimation where null features can occur in an arbitrary order, is a challenging problem in generative machine learning. Prior work on OADE has encoded feature identity (e.g., pixel location) by assigning each feature to a distinct fixed position in an input vector. As a result, architectures built for these inputs must strategically mask either null...
Paper Details
Title
The DEformer: An Order-Agnostic Distribution Estimating Transformer
Published Date
Jun 13, 2021
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