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  2. Quantum neural network - Wikipedia

    en.wikipedia.org/wiki/Quantum_neural_network

    A key difference lies in communication between the layers of a neural networks. For classical neural networks, at the end of a given operation, the current perceptron copies its output to the next layer of perceptron(s) in the network. However, in a quantum neural network, where each perceptron is a qubit, this would violate the no-cloning theorem.

  3. Activation function - Wikipedia

    en.wikipedia.org/wiki/Activation_function

    The activation function of a node in an artificial neural network is a function that calculates the output of the node based on its individual inputs and their weights. Nontrivial problems can be solved using only a few nodes if the activation function is nonlinear .

  4. Neural network quantum states - Wikipedia

    en.wikipedia.org/wiki/Neural_network_quantum_states

    Neural Network Quantum States (NQS or NNQS) is a general class of variational quantum states parameterized in terms of an artificial neural network.It was first introduced in 2017 by the physicists Giuseppe Carleo and Matthias Troyer [1] to approximate wave functions of many-body quantum systems.

  5. Quantum machine learning - Wikipedia

    en.wikipedia.org/wiki/Quantum_machine_learning

    Quantum neural networks apply the principals quantum information and quantum computation to classical neurocomputing. [72] Current research shows that QNN can exponentially increase the amount of computing power and the degrees of freedom for a computer, which is limited for a classical computer to its size. [72]

  6. Category:Artificial neural networks - Wikipedia

    en.wikipedia.org/wiki/Category:Artificial_neural...

    Capsule neural network; Catastrophic interference; Cellular neural network; Cerebellar model articulation controller; CoDi; Committee machine; Competitive learning; Compositional pattern-producing network; Computational cybernetics; Computational neurogenetic modeling; Confabulation (neural networks) Connectionist temporal classification ...

  7. Mathematics of artificial neural networks - Wikipedia

    en.wikipedia.org/wiki/Mathematics_of_artificial...

    Networks such as the previous one are commonly called feedforward, because their graph is a directed acyclic graph. Networks with cycles are commonly called recurrent. Such networks are commonly depicted in the manner shown at the top of the figure, where is shown as dependent upon itself. However, an implied temporal dependence is not shown.

  8. Quantum algorithm - Wikipedia

    en.wikipedia.org/wiki/Quantum_algorithm

    In quantum computing, a quantum algorithm is an algorithm that runs on a realistic model of quantum computation, the most commonly used model being the quantum circuit model of computation. [ 1 ] [ 2 ] A classical (or non-quantum) algorithm is a finite sequence of instructions, or a step-by-step procedure for solving a problem, where each step ...

  9. Quantum network - Wikipedia

    en.wikipedia.org/wiki/Quantum_network

    Quantum networks facilitate the transmission of information in the form of quantum bits, also called qubits, between physically separated quantum processors. A quantum processor is a machine able to perform quantum circuits on a certain number of qubits. Quantum networks work in a similar way to classical networks.