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  2. Neural coding - Wikipedia

    en.wikipedia.org/wiki/Neural_coding

    The temporal structure of a spike train or firing rate evoked by a stimulus is determined both by the dynamics of the stimulus and by the nature of the neural encoding process. Stimuli that change rapidly tend to generate precisely timed spikes [28] (and rapidly changing firing rates in PSTHs) no matter what neural coding strategy is being used ...

  3. Quoc V. Le - Wikipedia

    en.wikipedia.org/wiki/Quoc_V._Le

    Lê Viết Quốc (born 1982), [1] or in romanized form Quoc Viet Le, is a Vietnamese-American computer scientist and a machine learning pioneer at Google Brain, which he established with others from Google. He co-invented the doc2vec [2] and seq2seq [3] models in natural language processing.

  4. Neural encoding - Wikipedia

    en.wikipedia.org/?title=Neural_encoding&redirect=no

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  5. Neuronal ensemble - Wikipedia

    en.wikipedia.org/wiki/Neuronal_ensemble

    However, the basic principle of ensemble encoding holds: large neuronal populations do better than single neurons. The emergence of specific neural assemblies is thought to provide the functional elements of brain activity that execute the basic operations of informational processing (see Fingelkurts An.A. and Fingelkurts Al.A., 2004; 2005). [1 ...

  6. Autoencoder - Wikipedia

    en.wikipedia.org/wiki/Autoencoder

    An autoencoder is a type of artificial neural network used to learn efficient codings of unlabeled data (unsupervised learning).An autoencoder learns two functions: an encoding function that transforms the input data, and a decoding function that recreates the input data from the encoded representation.

  7. Recurrent neural network - Wikipedia

    en.wikipedia.org/wiki/Recurrent_neural_network

    Fully recurrent neural networks (FRNN) connect the outputs of all neurons to the inputs of all neurons. In other words, it is a fully connected network. This is the most general neural network topology, because all other topologies can be represented by setting some connection weights to zero to simulate the lack of connections between those ...

  8. Attention (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Attention_(machine_learning)

    [19] [20] [21] A slow neural network learns by gradient descent to generate keys and values for computing the weight changes of the fast neural network which computes answers to queries. [17] This was later shown to be equivalent to the unnormalized linear Transformer. [22] A follow-up paper developed a similar system with active weight ...

  9. Seq2seq - Wikipedia

    en.wikipedia.org/wiki/Seq2seq

    Shannon's diagram of a general communications system, showing the process by which a message sent becomes the message received (possibly corrupted by noise). seq2seq is an approach to machine translation (or more generally, sequence transduction) with roots in information theory, where communication is understood as an encode-transmit-decode process, and machine translation can be studied as a ...