User profiles for Corey Lammie
Corey LammieIBM Research - Zurich Verified email at ibm.com Cited by 834 |
Hardware implementation of deep network accelerators towards healthcare and biomedical applications
The advent of dedicated Deep Learning (DL) accelerators and neuromorphic processors
has brought on new opportunities for applying both Deep and Spiking Neural Network (SNN) …
has brought on new opportunities for applying both Deep and Spiking Neural Network (SNN) …
[HTML][HTML] Game changers in science and technology-now and beyond
The recent devastating pandemic has drastically reminded humanity of the importance of
constant scientific and technological progress. A strong interdisciplinary dialogue between …
constant scientific and technological progress. A strong interdisciplinary dialogue between …
MemTorch: An open-source simulation framework for memristive deep learning systems
Memristive devices have shown great promise to facilitate the acceleration and improve the
power efficiency of Deep Learning (DL) systems. Crossbar architectures constructed using …
power efficiency of Deep Learning (DL) systems. Crossbar architectures constructed using …
Efficient FPGA implementations of pair and triplet-based STDP for neuromorphic architectures
Synaptic plasticity is envisioned to bring about learning and memory in the brain. Various
plasticity rules have been proposed, among which spike-timing-dependent plasticity (STDP) …
plasticity rules have been proposed, among which spike-timing-dependent plasticity (STDP) …
Memtorch: A simulation framework for deep memristive cross-bar architectures
C Lammie, MR Azghadi�- 2020 IEEE international symposium�…, 2020 - ieeexplore.ieee.org
Memristive devices arranged in cross-bar architectures have shown great promise to facilitate
the acceleration and improve the power efficiency of Deep Learning (DL) systems for …
the acceleration and improve the power efficiency of Deep Learning (DL) systems for …
[PDF][PDF] Low-Power and High-Speed Deep FPGA Inference Engines for Weed Classification at the Edge.
Deep Neural Networks (DNNs) have recently achieved remarkable performance in a myriad
of applications, ranging from image recognition to language processing. Training such …
of applications, ranging from image recognition to language processing. Training such …
Memristive stochastic computing for deep learning parameter optimization
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 logic…
computation of various arithmetic operations using stochastic bit streams and digital logic…
[HTML][HTML] Modeling and simulating in-memory memristive deep learning systems: An overview of current efforts
Deep Learning (DL) systems have demonstrated unparalleled performance in many challenging
engineering applications. As the complexity of these systems inevitably increase, they …
engineering applications. As the complexity of these systems inevitably increase, they …
Seizure detection and prediction by parallel memristive convolutional neural networks
During the past two decades, epileptic seizure detection and prediction algorithms have
evolved rapidly. However, despite significant performance improvements, their hardware …
evolved rapidly. However, despite significant performance improvements, their hardware …
Unsupervised character recognition with a simplified FPGA neuromorphic system
C Lammie, T Hamilton…�- 2018 IEEE International�…, 2018 - ieeexplore.ieee.org
Neuromorphic hardware platforms have demonstrated significant promise in cognitive tasks
such as visual processing and classification. These platforms usually consist of several …
such as visual processing and classification. These platforms usually consist of several …