Neuro-inspired computing: From resistive memory to optics
- Charles Mackin
- Pritish Narayanan
- et al.
- 2019
- CLEO/Europe-EQEC 2019
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51 results for Pritish Narayanan
Accelerating deep neural networks with analog memory devices
- Geoffrey W. Burr
- Stefano Ambrogio
- et al.
- 2019
- CSTIC 2019
Training fully connected networks with resistive memories: Impact of device failures
- Louis P. Romero
- Stefano Ambrogio
- et al.
- 2019
- Faraday Discussions
Perspective on training fully connected networks with resistive memories: Device requirements for multiple conductances of varying significance
- Giorgio Cristiano
- Massimo Giordano
- et al.
- 2018
- Journal of Applied Physics
Recent progress in analog memory-based accelerators for deep learning
- Hsinyu Tsai
- Stefano Ambrogio
- et al.
- 2018
- Journal of Physics D: Applied Physics
Equivalent-accuracy accelerated neural-network training using analogue memory
- Stefano Ambrogio
- Pritish Narayanan
- et al.
- 2018
- Nature
Bidirectional non-filamentary RRAM as an analog neuromorphic synapse, Part I: Al/Mo/Pr0.7Ca0.3MnO3 material improvements and device measurements
- K. Moon
- Alessandro Fumarola
- et al.
- 2018
- IEEE J-EDS
Bidirectional Non-Filamentary RRAM as an Analog Neuromorphic Synapse, Part II: Impact of Al/Mo/Pr0.7Ca0.3MnO3 Device Characteristics on Neural Network Training Accuracy
- Alessandro Fumarola
- S. Sidler
- et al.
- 2018
- IEEE J-EDS
Improved deep neural network hardware-Accelerators based on non-volatile-memory: The local gains technique
- Irem Boybat
- Carmelo Di Nolfo
- et al.
- 2017
- ICRC 2017
Neuromorphic devices and architectures for next-generation cognitive computing
- Geoffrey W. Burr
- Pritish Narayanan
- et al.
- 2017
- ISCAS 2017