Keyword Analysis & Research: neural symbolic modeling

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How does the neuro-symbolic concept learner ( NS-CL ) work?

We propose the Neuro-Symbolic Concept Learner (NS-CL), a model that learns visual concepts, words, and semantic parsing of sentences without explicit supervision on any of them; instead, our model learns by simply looking at images and reading paired questions and answers.

How is a neural network learns a symbolic expression?

An illustration of how our technique learns a symbolic expression: first, a neural network undergoes supervised learning, then, symbolic regression approximates internal functions of the model.

Are there any machine learning algorithms for symbolic models?

“ Symbolic regression ” is one such machine learning algorithm for symbolic models: it’s a supervised technique that assembles analytic functions to model a dataset.

How is neuro symbolic reasoning used in AI?

According to the paper, it helps AI recognize objects in videos, analyze their movement, and reason about their behaviours. They used CLEVRER to benchmark the performances of neural networks and neuro-symbolic reasoning by using only a fraction of the data required for traditional deep learning systems.


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