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  2. Graph (abstract data type) - Wikipedia

    en.wikipedia.org/wiki/Graph_(abstract_data_type)

    In computer science, a graph is an abstract data type that is meant to implement the undirected graph and directed graph concepts from the field of graph theory within mathematics. A graph data structure consists of a finite (and possibly mutable) set of vertices (also called nodes or points ), together with a set of unordered pairs of these ...

  3. Graph neural network - Wikipedia

    en.wikipedia.org/wiki/Graph_neural_network

    In the more general subject of "geometric deep learning", certain existing neural network architectures can be interpreted as GNNs operating on suitably defined graphs. [12] A convolutional neural network layer, in the context of computer vision , can be considered a GNN applied to graphs whose nodes are pixels and only adjacent pixels are ...

  4. Feature learning - Wikipedia

    en.wikipedia.org/wiki/Feature_learning

    The goal of many graph representation learning techniques is to produce an embedded representation of each node based on the overall network topology. [39] node2vec extends the word2vec training technique to nodes in a graph by using co-occurrence in random walks through the graph as the measure of association. [40]

  5. Scientific modelling - Wikipedia

    en.wikipedia.org/wiki/Scientific_modelling

    There is also an increasing attention to scientific modelling [4] in fields such as science education, [5] philosophy of science, systems theory, and knowledge visualization. There is a growing collection of methods , techniques and meta- theory about all kinds of specialized scientific modelling.

  6. Knowledge graph embedding - Wikipedia

    en.wikipedia.org/wiki/Knowledge_graph_embedding

    The vector representation of the entities and relations can be used for different machine learning applications. In representation learning, knowledge graph embedding (KGE), also referred to as knowledge representation learning (KRL), or multi-relation learning, [1] is a machine learning task of learning a low-dimensional representation of a ...

  7. Knowledge graph - Wikipedia

    en.wikipedia.org/wiki/Knowledge_graph

    In knowledge representation and reasoning, a knowledge graph is a knowledge base that uses a graph-structured data model or topology to represent and operate on data. Knowledge graphs are often used to store interlinked descriptions of entities – objects, events, situations or abstract concepts – while also encoding the free-form semantics ...

  8. Graphical model - Wikipedia

    en.wikipedia.org/wiki/Graphical_model

    A chain graph is a graph which may have both directed and undirected edges, but without any directed cycles (i.e. if we start at any vertex and move along the graph respecting the directions of any arrows, we cannot return to the vertex we started from if we have passed an arrow). Both directed acyclic graphs and undirected graphs are special ...

  9. GCSE Science - Wikipedia

    en.wikipedia.org/wiki/GCSE_Science

    Triple Award Science, commonly referred to as Triple Science, results in three separate GCSEs in Biology, Chemistry and Physics and provide the broadest coverage of the main three science subjects. The qualifications are offered by the five main awarding bodies in England; AQA , Edexcel , OCR , CIE and Eduqas .