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  2. Graph neural network - Wikipedia

    en.wikipedia.org/wiki/Graph_neural_network

    Graph attention network is a combination of a graph neural network and an attention layer. The implementation of attention layer in graphical neural networks helps provide attention or focus to the important information from the data instead of focusing on the whole data.

  3. 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 ...

  4. Outline of machine learning - Wikipedia

    en.wikipedia.org/wiki/Outline_of_machine_learning

    Machine learning (ML) is a subfield of artificial intelligence within computer science that evolved from the study of pattern recognition and computational learning theory. [1] In 1959, Arthur Samuel defined machine learning as a "field of study that gives computers the ability to learn without being explicitly programmed". [ 2 ]

  5. Differentiable programming - Wikipedia

    en.wikipedia.org/wiki/Differentiable_programming

    Static, compiled graph-based approaches such as TensorFlow, [note 1] Theano, and MXNet. They tend to allow for good compiler optimization and easier scaling to large systems, but their static nature limits interactivity and the types of programs that can be created easily (e.g. those involving loops or recursion ), as well as making it harder ...

  6. Machine learning - Wikipedia

    en.wikipedia.org/wiki/Machine_learning

    Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalize to unseen data, and thus perform tasks without explicit instructions. [1]

  7. Learning curve (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Learning_curve_(machine...

    In machine learning (ML), a learning curve (or training curve) is a graphical representation that shows how a model's performance on a training set (and usually a validation set) changes with the number of training iterations (epochs) or the amount of training data. [1]

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  9. 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 ...