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Brian Hoskins
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2020 – today
- 2024
- [i10]Osama Yousuf
, Brian Hoskins, Karthick Ramu, Mitchell Fream, William A. Borders, Advait Madhavan, Matthew W. Daniels, Andrew Dienstfrey, Jabez J. McClelland, Martin Lueker-Boden, Gina C. Adam:
Layer Ensemble Averaging for Improving Memristor-Based Artificial Neural Network Performance. CoRR abs/2404.15621 (2024) - 2023
- [j1]Siyuan Huang
Low-Rank Gradient Descent for Memory-Efficient Training of Deep In-Memory Arrays. ACM J. Emerg. Technol. Comput. Syst. 19(2): 16:1-16:24 (2023) - [i9]William A. Borders, Advait Madhavan, Matthew W. Daniels
Experimental demonstration of a robust training method for strongly defective neuromorphic hardware. CoRR abs/2312.06446 (2023) - 2022
- [c8]Wen Ma, Tung Thanh Hoang, Brian Hoskins, Matthew W. Daniels
Effect of OTS Selector Reliabilities on NVM Crossbar-based Neuromorphic Training. IRPS 2022: 35-1 - 2021
- [c7]Brian Hoskins, Wen Ma, Mitchell Fream, Osama Yousuf
A System for Validating Resistive Neural Network Prototypes. ICONS 2021: 26:1-26:5 - [i8]Jonathan M. Goodwill, Nitin Prasad, Brian D. Hoskins, Matthew W. Daniels, Advait Madhavan, Lei Wan, Tiffany S. Santos, Michael Tran, Jordan A. Katine, Patrick M. Braganca, Mark D. Stiles, Jabez J. McClelland:
Implementation of a Binary Neural Network on a Passive Array of Magnetic Tunnel Junctions. CoRR abs/2112.09159 (2021) - 2020
- [c6]Siyuan Huang, Brian D. Hoskins, Matthew W. Daniels, Mark D. Stiles, Gina C. Adam:
Streaming Batch Gradient Tracking for Neural Network Training (Student Abstract). AAAI 2020: 13813-13814 - [i7]Siyuan Huang, Brian D. Hoskins, Matthew W. Daniels, Mark D. Stiles, Gina C. Adam:
Memory-efficient training with streaming dimensionality reduction. CoRR abs/2004.12041 (2020)
2010 – 2019
- 2019
- [i6]Brian D. Hoskins, Matthew W. Daniels
Streaming Batch Eigenupdates for Hardware Neuromorphic Networks. CoRR abs/1903.01635 (2019) - 2018
- [c5]Dasheng Li, Georg Ramer
Nanoscale Scanning Probe Thermometry of TaOe-based selector devices. DRC 2018: 1-2 - [i5]Alice Mizrahi, Thomas Marsh, Brian Hoskins, Mark D. Stiles:
A scalable method to find the shortest path in a graph with circuits of memristors. CoRR abs/1809.04677 (2018) - 2017
- [c4]Gina C. Adam
Utilizing I-V non-linearity and analog state variations in ReRAM-based security primitives. ESSDERC 2017: 74-77 - 2016
- [c3]Gina C. Adam
Highly-uniform multi-layer ReRAM crossbar circuits. ESSDERC 2016: 436-439 - [c2]Mirko Prezioso, Y. Zhong, D. Gavrilov, Farnood Merrikh-Bayat, Brian Hoskins
Spiking neuromorphic networks with metal-oxide memristors. ISCAS 2016: 177-180 - 2015
- [i4]Mirko Prezioso, Farnood Merrikh-Bayat, Brian Hoskins, Konstantin K. Likharev, Dmitri B. Strukov:
Self-Adaptive Spike-Time-Dependent Plasticity of Metal-Oxide Memristors. CoRR abs/1505.05549 (2015) - [i3]Gina C. Adam
Three-Dimensional Stateful Material Implication Logic. CoRR abs/1509.02986 (2015) - 2014
- [i2]Mirko Prezioso, Farnood Merrikh-Bayat, Brian Hoskins, Gina C. Adam, Konstantin K. Likharev, Dmitri B. Strukov:
Training and Operation of an Integrated Neuromorphic Network Based on Metal-Oxide Memristors. CoRR abs/1412.0611 (2014) - 2013
- [c1]Ligang Gao, Farnood Merrikh-Bayat, Fabien Alibart, Xinjie Guo, Brian D. Hoskins
Digital-to-analog and analog-to-digital conversion with metal oxide memristors for ultra-low power computing. NANOARCH 2013: 19-22 - 2011
- [i1]Fabien Alibart, Ligang Gao, Brian Hoskins, Dmitri B. Strukov:
High-Precision Tuning of State for Memristive Devices by Adaptable Variation-Tolerant Algorithm. CoRR abs/1110.1393 (2011)
Coauthor Index
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