… neural network architecture that can learn to recognize and robustly generate precisely timed
events separated by significant time … tasks involving long time lags between relevant input …

… So, there is useful information in the spike rate that cannot be captured by the precise
timing of single spikes. Encoding information in the precise timing of multiple spikes which are …

… at the other, and mixed-precision in between, we … precision, namely anyprecision deep
neural networks. After training, we can freely quantize the model layers into various precision …

… In the following, we introduce a class of spiking neural network models for which a wide
range of dynamical phenomena becomes analytically accessible. We briefly list related model …

… position estimation scheme for timing-belt drives using artificial neural networks. In this …
neural network topology accepting input from a position sensor on the actuator side of the timing …

… We propose precision gating (PG), an end-to-end trainable dynamic dual-precision quantization
technique for deep neural networks. PG computes most features in a low precision and …

… precisely because timing is critical to so many forms of processing, it is a general computation
performed by recurrent neural networks… framework of recurrent networks that may be …

… new neural network based precise timing generation framework, named the Timing Generating
Network (… In this paper, we propose a novel framework of a neural network-based timing …

… simulation of chaotic dynamics by neural network techniques. For this purpose… neural network
techniques adapted to time series, namely, reservoir computing [using Echo State Network …

… A) could reflect that these two coordination modes share neural mechanisms. Notably,
both these patterns, in contrast to In-phase, require that a sequence of precisely timed, …