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Role of delay-times in delay-based photonic reservoir computing
Delay-based reservoir computing has gained a lot of attention due to the relative simplicity
with which this concept can be implemented in hardware. However, unnecessary constraints …
with which this concept can be implemented in hardware. However, unnecessary constraints …
Theory of neuromorphic computing by waves: machine learning by rogue waves, dispersive shocks, and solitons
We study artificial neural networks with nonlinear waves as a computing reservoir. We
discuss universality and the conditions to learn a dataset in terms of output channels and …
discuss universality and the conditions to learn a dataset in terms of output channels and …
Irreversibility, heat and information flows induced by non-reciprocal interactions
We study the thermodynamic properties induced by non-reciprocal interactions between
stochastic degrees of freedom in time-and space-continuous systems. We show that, under …
stochastic degrees of freedom in time-and space-continuous systems. We show that, under …
Photonic extreme learning machine by free-space optical propagation
Photonic brain-inspired platforms are emerging as novel analog computing devices,
enabling fast and energy-efficient operations for machine learning. These artificial neural …
enabling fast and energy-efficient operations for machine learning. These artificial neural …
Networks of random lasers: current perspective and future challenges
Artificial neural networks are widely used in many different applications because of their
ability to deal with a range of complex problems generally involving massive data sets …
ability to deal with a range of complex problems generally involving massive data sets …
Reducing reservoir computer hyperparameter dependence by external timescale tailoring
Task specific hyperparameter tuning in reservoir computing is an open issue, and is of
particular relevance for hardware implemented reservoirs. We investigate the influence of …
particular relevance for hardware implemented reservoirs. We investigate the influence of …
[HTML][HTML] Reservoir computing with delayed input for fast and easy optimisation
Reservoir computing is a machine learning method that solves tasks using the response of a
dynamical system to a certain input. As the training scheme only involves optimising the …
dynamical system to a certain input. As the training scheme only involves optimising the …
Chaotic attractor reconstruction using small reservoirs—the influence of topology
Forecasting timeseries based upon measured data is needed in a wide range of
applications and has been the subject of extensive research. A particularly challenging task …
applications and has been the subject of extensive research. A particularly challenging task …
Large-scale photonic natural language processing
Modern machine-learning applications require huge artificial networks demanding
computational power and memory. Light-based platforms promise ultrafast and energy …
computational power and memory. Light-based platforms promise ultrafast and energy …
All-optical spiking neuron based on passive microresonator
Neuromorphic photonics that aims to process and store information simultaneously like
human brains has emerged as a promising alternative for next generation intelligent …
human brains has emerged as a promising alternative for next generation intelligent …