Abhronil Sengupta
Pennsylvania State University
138 Papers
568 Citations
Abhronil Sengupta is an academic researcher from Pennsylvania State University. The author has contributed to research in topics: Neuromorphic engineering & Computer science. The author has an hindex of 30, co-authored 105 publications. Previous affiliations of Abhronil Sengupta include Jadavpur University & Indian Institute of Technology Kharagpur.
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Papers
Going Deeper in Spiking Neural Networks: VGG and Residual Architectures.
TL;DR: In this paper, the authors propose a novel algorithmic technique for generating an SNN with a deep architecture, and demonstrate its effectiveness on complex visual recognition problems such as CIFAR-10 and ImageNet.
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Going Deeper in Spiking Neural Networks: VGG and Residual Architectures
TL;DR: A novel algorithmic technique is proposed for generating an SNN with a deep architecture with significantly better accuracy than the state-of-the-art, and its effectiveness on complex visual recognition problems such as CIFAR-10 and ImageNet is demonstrated.
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Magnetic Tunnel Junction Based Long-Term Short-Term Stochastic Synapse for a Spiking Neural Network with On-Chip STDP Learning
TL;DR: This work proposes a heterostructure composed of a Magnetic Tunnel Junction and a heavy metal as a stochastic binary synapse comprising two unique binary synaptic elements, in order to improve the synaptic learning efficiency.
Magnetic Tunnel Junction Mimics Stochastic Cortical Spiking Neurons.
TL;DR: This work demonstrates the mapping of the probabilistic spiking nature of pyramidal neurons in the cortex to the stochastic switching behavior of a Magnetic Tunnel Junction in presence of thermal noise.
Toward Fast Neural Computing using All-Photonic Phase Change Spiking Neurons.
TL;DR: In this article, the phase change dynamics of Ge2Sb2Te5 (GST) embedded on top of a microring resonator is exploited to alleviate the energy constraints of PCMs in electrical domain.