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Incorporating Domain Knowledge into Deep Neural Networks

2021-02-27 10:39:43
Tirtharaj Dash, Sharad Chitlangia, Aditya Ahuja, Ashwin Srinivasan
arXiv_AI
     
Abstract

We present a survey of ways in which domain-knowledge has been included when constructing models with neural networks. The inclusion of domain-knowledge is of special interest not just to constructing scientific assistants, but also, many other areas that involve understanding data using human-machine collaboration. In many such instances, machine-based model construction may benefit significantly from being provided with human-knowledge of the domain encoded in a sufficiently precise form. This paper examines two broad approaches to encode such knowledge--as logical and numerical constraints--and describes techniques and results obtained in several sub-categories under each of these approaches.

Abstract (translated)

URL

https://arxiv.org/abs/2103.00180

PDF

https://arxiv.org/pdf/2103.00180.pdf

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