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  2. Topological deep learning - Wikipedia

    en.wikipedia.org/wiki/Topological_Deep_Learning

    Learning Tasks on topological domains can be broadly classified into three categories : cell classification, cell prediction and complex classification. [1] Focusing on topology in the sense of point set topology, an active branch of TDL is concerned with learning on topological spaces, that is, on different topological domains.

  3. Recursive neural network - Wikipedia

    en.wikipedia.org/wiki/Recursive_neural_network

    A recursive neural network is a kind of deep neural network created by applying the same set of weights recursively over a structured input, to produce a structured prediction over variable-size input structures, or a scalar prediction on it, by traversing a given structure in topological order.

  4. Network topology - Wikipedia

    en.wikipedia.org/wiki/Network_topology

    Network topology is the arrangement of the elements (links, nodes, etc.) of a communication network. [1] [2] Network topology can be used to define or describe the arrangement of various types of telecommunication networks, including command and control radio networks, [3] industrial fieldbusses and computer networks.

  5. Data center network architectures - Wikipedia

    en.wikipedia.org/wiki/Data_center_network...

    Fat tree DCN employs commodity network switches based architecture using Clos topology. [3] The network elements in fat tree topology also follows hierarchical organization of network switches in access, aggregate, and core layers. However, the number of network switches is much larger than the three-tier DCN.

  6. Neural machine translation - Wikipedia

    en.wikipedia.org/wiki/Neural_machine_translation

    Neural machine translation (NMT) is an approach to machine translation that uses an artificial neural network to predict the likelihood of a sequence of words, typically modeling entire sentences in a single integrated model.

  7. Topological data analysis - Wikipedia

    en.wikipedia.org/wiki/Topological_data_analysis

    The initial motivation is to study the shape of data. TDA has combined algebraic topology and other tools from pure mathematics to allow mathematically rigorous study of "shape". The main tool is persistent homology, an adaptation of homology to point cloud data. Persistent homology has been applied to many types of data across many fields.

  8. Layer (deep learning) - Wikipedia

    en.wikipedia.org/wiki/Layer_(Deep_Learning)

    A layer in a deep learning model is a structure or network topology in the model's architecture, which takes information from the previous layers and then passes it to the next layer. Layer types [ edit ]

  9. Network architecture - Wikipedia

    en.wikipedia.org/wiki/Network_architecture

    Network architecture is the design of a computer network.It is a framework for the specification of a network's physical components and their functional organization and configuration, its operational principles and procedures, as well as communication protocols used.