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Open AccessJournal ArticleDOI

A neural compiler

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TLDR
This paper describes a neural compiler, a compiler that produces a neural network that computes what is specified by the PASCAL program and generates an intermediate code called cellular code.
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This article is published in Theoretical Computer Science.The article was published on 1995-04-17 and is currently open access. It has received 41 citations till now. The article focuses on the topics: Compiler & Bootstrapping (compilers).

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Citations
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Journal ArticleDOI

Automatic definition of modular neural networks

TL;DR: An artificial developmental system that is a computationally efficient technique for the automatic generation of complex artificial neural networks (ANNs) and some simulation results showing that the same problem cannot be solved if the mechanism for automatic definition of subnetworks is suppressed.
Proceedings ArticleDOI

Learning Natural Coding Conventions

TL;DR: NATURALIZE as mentioned in this paper is a framework that learns the style of a codebase and suggests revisions to improve stylistic consistency, which can even transfer knowledge about coding conventions across projects.
Proceedings Article

Programming with a differentiable forth interpreter

TL;DR: In this article, an end-to-end differentiable interpreter for the programming language Forth is presented, which enables programmers to write program sketches with slots that can be filled with behaviour trained from program input-output data.
Posted Content

Learning Continuous Semantic Representations of Symbolic Expressions

TL;DR: An exhaustive evaluation on the task of checking equivalence on a highly diverse class of symbolic algebraic and boolean expression types is performed, showing that the proposed neural equivalence networks model significantly outperforms existing architectures.
Posted Content

Programming with a Differentiable Forth Interpreter

TL;DR: An end-to-end differentiable interpreter for the programming language Forth which enables programmers to write program sketches with slots that can be filled with behaviour trained from program input-output data, and shows empirically that this interpreter is able to effectively leverage different levels of prior program structure and learn complex behaviours such as sequence sorting and addition.
References
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Journal ArticleDOI

A logical calculus of the ideas immanent in nervous activity

TL;DR: In this article, it is shown that many particular choices among possible neurophysiological assumptions are equivalent, in the sense that for every net behaving under one assumption, there exists another net which behaves under another and gives the same results, although perhaps not in the same time.
Journal ArticleDOI

The perceptron: a probabilistic model for information storage and organization in the brain.

TL;DR: This article will be concerned primarily with the second and third questions, which are still subject to a vast amount of speculation, and where the few relevant facts currently supplied by neurophysiology have not yet been integrated into an acceptable theory.
Book

The perception: a probabilistic model for information storage and organization in the brain

F. Rosenblatt
TL;DR: The second and third questions are still subject to a vast amount of speculation, and where the few relevant facts currently supplied by neurophysiology have not yet been integrated into an acceptable theory as mentioned in this paper.
Book

Perceptrons: An Introduction to Computational Geometry

TL;DR: The aim of this book is to seek general results from the close study of abstract version of devices known as perceptrons.
Book ChapterDOI

Representation of Events in Nerve Nets and Finite Automata

S. C. Kleene
TL;DR: This memorandum is devoted to an elementary exposition of the problems and of results obtained on the McCulloch-Pitts nerve net during investigations in August 1951.