Abstract. Long Short-Term Memory (LSTM) recurrent neural networks (RNNs) are local in space and time and closely related to a biological model of memory in the prefrontal cortex. N...
Most neural communication and processing tasks are driven by spikes. This has enabled the application of the event-driven simulation schemes. However the simulation of spiking neu...
Richard R. Carrillo, Eduardo Ros, Boris Barbour, C...
This paper presents our approach towards realizing a robot which can bootstrap itself towards higher complexity through embodied interaction dynamics with the environment includin...
This work proposes a novel practical and general-purpose lossless compression algorithm named Neural Markovian Predictive Compression (NMPC), based on a novel combination of Bayesi...
Abstract— In this paper, automated micro-sized objects manipulation is investigated. The novelty of the proposed method lies on the compensation of all the nonlinear scaling forc...