Add to ORKGTrabajo presentado en la 84th Annual Meeting of the DPG and DPG Meeting of the Condensed Matter Section, SKM (SYNC 1: Symposium: Advanced neuromorphic computing hardware: Towards efficient machine learning), celebrada online del 27 de septiembre al 1 de octubre.Advances in Machine Learning have recently boosted neuromorphic computing and its implementation in analog hardware. We discuss why physics and complex systems science provide valuable perspectives and tools for understanding existing methods and developing novel transdisciplinary approaches and their hardware implementation
Recent progress in artificial intelligence is largely attributed to the rapid development of machine...
Neuromorphic hardware enables novel modes of computation. We present two innovative learning strate...
In the face of increasingly large computational demands and the impending halt to Moore's law, the s...
The success of deep networks and recent industry involvement in brain-inspired computing is igniting...
This talk will provide a historical overview of developments in neurophysiology since the 17th centu...
After their inception in the 1940s and several decades of moderate success, artificial neural networ...
Neuromorphic engineering attempts to understand the computational properties of neural processing sy...
The ongoing revolution in Deep Learning is redefining the nature of computing that is driven by the ...
Abstract Neuromorphic systems are currently experiencing a rapid upswing due to the fact that today'...
Artificial intelligence (AI) has the ability of revolutionizing our lives and society in a radical w...
The rapid development in the field of artificial intelligence has increased the demand for neuromorp...
© 2019 IEEEMachine learning has emerged as the dominant tool for implementing complex cognitive task...
Inspired by the working principles of the human brain, neuromorphic computing shows great potential ...
Recent progress in artificial intelligence is largely attributed to the rapid development of machine...
Neuromorphic hardware enables novel modes of computation. We present two innovative learning strate...
In the face of increasingly large computational demands and the impending halt to Moore's law, the s...
The success of deep networks and recent industry involvement in brain-inspired computing is igniting...
This talk will provide a historical overview of developments in neurophysiology since the 17th centu...
After their inception in the 1940s and several decades of moderate success, artificial neural networ...
Neuromorphic engineering attempts to understand the computational properties of neural processing sy...
The ongoing revolution in Deep Learning is redefining the nature of computing that is driven by the ...
Abstract Neuromorphic systems are currently experiencing a rapid upswing due to the fact that today'...
Artificial intelligence (AI) has the ability of revolutionizing our lives and society in a radical w...
The rapid development in the field of artificial intelligence has increased the demand for neuromorp...
© 2019 IEEEMachine learning has emerged as the dominant tool for implementing complex cognitive task...
Inspired by the working principles of the human brain, neuromorphic computing shows great potential ...
Recent progress in artificial intelligence is largely attributed to the rapid development of machine...
Neuromorphic hardware enables novel modes of computation. We present two innovative learning strate...
In the face of increasingly large computational demands and the impending halt to Moore's law, the s...