531 citations · 1.6k across the 49 of their papers we have counts for
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Seizure Detection and Prediction by Parallel Memristive Convolutional Neural Networks
Chenqi Li, Corey Lammie, Xuening Dong +3
During the past two decades, epileptic seizure detection and prediction algorithms have evolved rapidly. However, despite significant performance improvements, their hardware imple…
Design Space Exploration of Dense and Sparse Mapping Schemes for RRAM Architectures
Corey Lammie, Jason K. Eshraghian, Chenqi Li +4
The impact of device and circuit-level effects in mixed-signal Resistive Random Access Memory (RRAM) accelerators typically manifest as performance degradation of Deep Learning (DL…
Memristive Stochastic Computing for Deep Learning Parameter Optimization
Corey Lammie, Jason K. Eshraghian, Wei D. Lu +1
Stochastic Computing (SC) is a computing paradigm that allows for the low-cost and low-power computation of various arithmetic operations using stochastic bit streams and digital l…
Towards Memristive Deep Learning Systems for Real-time Mobile Epileptic Seizure Prediction
Corey Lammie, Wei Xiang, Mostafa Rahimi Azghadi
The unpredictability of seizures continues to distress many people with drug-resistant epilepsy. On account of recent technological advances, considerable efforts have been made us…
MemTorch: An Open-source Simulation Framework for Memristive Deep Learning Systems
Corey Lammie, Wei Xiang, Bernabé Linares-Barranco +1
Memristive devices have shown great promise to facilitate the acceleration and improve the power efficiency of Deep Learning (DL) systems. Crossbar architectures constructed using…
Variation-aware Binarized Memristive Networks
Corey Lammie, Olga Krestinskaya, Alex James +1
The quantization of weights to binary states in Deep Neural Networks (DNNs) can replace resource-hungry multiply accumulate operations with simple accumulations. Such Binarized Neu…