Wave-based analog signal processing holds the promise of extremely fast, on-the-fly, power-efficient data processing, occurring as a wave propagates through an artificially engineered medium. Yet, due to the fundamentally weak non-linearities of traditional wave materials, such analog processors have been so far largely confined to simple linear projections such as image edge detection or matrix multiplications. Complex neuromorphic computing tasks, which inherently require strong non-linearities, have so far remained out-of-reach of wave-based solutions, with a few attempts that implemented non-linearities on the digital front, or used weak and inflexible non-linear sensors, restraining the learning performance. Here, we tackle this issue ...
We present a complex network of interconnected optical structures for information processing. This n...
We demonstrate an improved technique for implementing logic circuits in light-sensitive chemical exc...
Complex scattering exists in many diverse physical and real-life scenarios. Examples include reactio...
We study artificial neural networks with nonlinear waves as a computing reservoir. We discuss univer...
In this paper we present a unified framework for extreme learning machines and reservoir computing (...
For many challenging problems where the mathematical description is not explicitly defined, artifici...
Nonlinear photonic delay systems present interesting implementation platforms for machine learning m...
Time stretch instruments have been exceptionally successful in discovering single-shot ultrafastphen...
Machine learning techniques have proven very efficient in assorted classification tasks. Nevertheles...
We demonstrate that time-delayed nonlinear effects in exciton-polaritons can be used to construct ne...
Reservoir computing is a recently introduced, highly efficient bio-inspired approach for processing ...
International audienceWe report on the experimental demonstration of a hybrid optoelectronic neuromo...
Reservoir computers (RCs) are randomized recurrent neural networks well adapted to process time seri...
The ability of deep neural networks to perform complex tasks more accurately than manually-crafted s...
Neural networks are currently implemented on digital Von Neumann machines, which do not fully levera...
We present a complex network of interconnected optical structures for information processing. This n...
We demonstrate an improved technique for implementing logic circuits in light-sensitive chemical exc...
Complex scattering exists in many diverse physical and real-life scenarios. Examples include reactio...
We study artificial neural networks with nonlinear waves as a computing reservoir. We discuss univer...
In this paper we present a unified framework for extreme learning machines and reservoir computing (...
For many challenging problems where the mathematical description is not explicitly defined, artifici...
Nonlinear photonic delay systems present interesting implementation platforms for machine learning m...
Time stretch instruments have been exceptionally successful in discovering single-shot ultrafastphen...
Machine learning techniques have proven very efficient in assorted classification tasks. Nevertheles...
We demonstrate that time-delayed nonlinear effects in exciton-polaritons can be used to construct ne...
Reservoir computing is a recently introduced, highly efficient bio-inspired approach for processing ...
International audienceWe report on the experimental demonstration of a hybrid optoelectronic neuromo...
Reservoir computers (RCs) are randomized recurrent neural networks well adapted to process time seri...
The ability of deep neural networks to perform complex tasks more accurately than manually-crafted s...
Neural networks are currently implemented on digital Von Neumann machines, which do not fully levera...
We present a complex network of interconnected optical structures for information processing. This n...
We demonstrate an improved technique for implementing logic circuits in light-sensitive chemical exc...
Complex scattering exists in many diverse physical and real-life scenarios. Examples include reactio...