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    Chapter and Conference Paper

    Gating Sensory Noise in a Spiking Subtractive LSTM

    Spiking neural networks are being investigated both as biologically plausible models of neural computation and also as a potentially more efficient type of neural network. Recurrent neural networks in the form...

    Isabella Pozzi, Roeland Nusselder in Artificial Neural Networks and Machine Lea… (2018)

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    Chapter and Conference Paper

    A Deep Predictive Coding Network for Inferring Hierarchical Causes Underlying Sensory Inputs

    Predictive coding has been argued as a mechanism underlying sensory processing in the brain. In computational models of predictive coding, the brain is described as a machine that constructs and continuously ...

    Shirin Dora, Cyriel Pennartz, Sander Bohte in Artificial Neural Networks and Machine Lea… (2018)

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    Chapter and Conference Paper

    Continuous-Time Spike-Based Reinforcement Learning for Working Memory Tasks

    As the brain purportedly employs on-policy reinforcement learning compatible with SARSA learning, and most interesting cognitive tasks require some form of memory while taking place in continuous-time, recent ...

    Marios Karamanis, Davide Zambrano in Artificial Neural Networks and Machine Lea… (2018)