Statistical Training for Neuromorphic Computing using Memristor-based Crossbars Considering Process Variations and Noise
Ying Zhu(Pacific Northwest National Laboratory), Ulf Schlichtmann(Technical University of Munich), Tsung-Yi Ho(National Tsing Hua University), Grace Li Zhang(Technical University of Munich), Bing Li(Technical University of Munich), Tianchen Wang(University of Notre Dame), Yiyu Shi(University of Notre Dame)
Cited by 56
Related Papers
Scaling for edge inference of deep neural networks
|Nature Electronics|2018|468
Ultrasensitive single-cell proteomics workflow identifies >1000 protein groups per mammalian cell
|Chemical Science|2020|245
Improved Single-Cell Proteome Coverage Using Narrow-Bore Packed NanoLC Columns and Ultrasensitive Mass Spectrometry
|Analytical Chemistry|2020|182
Hardware/Software Co-Exploration of Neural Architectures
|IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems|2020|148
Spatially Resolved Proteome Mapping of Laser Capture Microdissected Tissue with Automated Sample Transfer to Nanodroplets
|Molecular & Cellular Proteomics|2018|142