A relation network (RN) is an artificial neural network component with a structure that can reason about relations among objects. An example category of such relations is spatial relations …

Jun 5, 2017 · Relational reasoning is a central component of generally intelligent behavior, but has proven difficult for neural networks to learn. In this paper we describe how to use Relation …

Relational Network Theory (RNT), also known as Neurocognitive Linguistics (NCL) and formerly as Stratificational Linguistics or Cognitive-Stratificational Linguistics, is a connectionist …

Nov 21, 2017 · We introduce the recurrent relational network, a general purpose module that operates on a graph representation of objects. As a generalization of Santoro et al. [2017]'s …

Jun 6, 2017 · In two new papers, we explore the ability for deep neural networks to perform complicated relational reasoning with unstructured data. In the first paper - A simple neural …

Implementation of Recurrent Relational Network. Original paper: https://arxiv.org/abs/1711.08028. This repository uses PyTorch v1.3 (Python3.7). This implementation tests the Relation …

Jul 1, 2017 · The authors present Relational Neural Network as a module. It can accept encoded objects and learn relations from them, but more importantly, they can be plugged into …

Apr 13, 2020 · The paper proposes a computational block which they call relational network (RN), which takes a set of object ($O$) as input and outputs a vector. The main computational unit in …

May 25, 2024 · Relational Neural Networks (RNs) address these shortcomings by computing explicit pairwise relationships between entities. This capability enhances their performance in …

Relation Network is a plug-n-play module to incorporate relational reasoning abilities to deep learning models. This repository implements Relation Network module in PyTorch for the Sort …