Training fully connected networks with resistive memories: Impact of device failures
- Louis P. Romero
- Stefano Ambrogio
- et al.
- 2019
- Faraday Discussions
Publications
178 results for Geoffrey W. Burr
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
Tutorial: Brain-inspired computing using phase-change memory devices
- 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
Enhancing Magnetic Light Emission with All-Dielectric Optical Nanoantennas
- Maria Sanz-Paz
- Cyrine Ernandes
- et al.
- 2018
- Nano Letters
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
Reducing circuit design complexity for neuromorphic machine learning systems based on Non-Volatile Memory arrays
- Pritish Narayanan
- Lucas L. Sanches
- et al.
- 2017
- ISCAS 2017