Bipin Rajendran

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New Jersey Institute of Technology ∙ King's College London

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SpinAPS: A High-Performance Spintronic Accelerator for Probabilistic Spiking Neural Networks

We discuss a high-performance and high-throughput hardware accelerator f...
08/05/2020 ∙ by Anakha V Babu, et al. ∙ 0 ∙ share

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Memristors – from In-memory computing, Deep Learning Acceleration, Spiking Neural Networks, to the Future of Neuromorphic and Bio-inspired Computing

Machine learning, particularly in the form of deep learning, has driven ...
04/30/2020 ∙ by Adnan Mehonic, et al. ∙ 23 ∙ share

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ESSOP: Efficient and Scalable Stochastic Outer Product Architecture for Deep Learning

Deep neural networks (DNNs) have surpassed human-level accuracy in a var...
03/25/2020 ∙ by Vinay Joshi, et al. ∙ 0 ∙ share

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Supervised Learning in Spiking Neural Networks with Phase-Change Memory Synapses

Spiking neural networks (SNN) are artificial computational models that h...
05/28/2019 ∙ by S. R. Nandakumar, et al. ∙ 0 ∙ share

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Low-Power Neuromorphic Hardware for Signal Processing Applications

Machine learning has emerged as the dominant tool for implementing compl...
01/11/2019 ∙ by Bipin Rajendran, et al. ∙ 2 ∙ share

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Training Multilayer Spiking Neural Networks using NormAD based Spatio-Temporal Error Backpropagation

Spiking neural networks (SNNs) have garnered a great amount of interest ...
10/23/2018 ∙ by Navin Anwani, et al. ∙ 0 ∙ share

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Learning First-to-Spike Policies for Neuromorphic Control Using Policy Gradients

Artificial Neural Networks (ANNs) are currently being used as function a...
10/23/2018 ∙ by Bleema Rosenfeld, et al. ∙ 0 ∙ share

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Adversarial Training for Probabilistic Spiking Neural Networks

Classifiers trained using conventional empirical risk minimization or ma...
02/22/2018 ∙ by Alireza Bagheri, et al. ∙ 0 ∙ share

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Stochastic Deep Learning in Memristive Networks

We study the performance of stochastically trained deep neural networks ...
11/09/2017 ∙ by Anakha V Babu, et al. ∙ 0 ∙ share

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Learning and Real-time Classification of Hand-written Digits With Spiking Neural Networks

We describe a novel spiking neural network (SNN) for automated, real-tim...
11/09/2017 ∙ by Shruti R. Kulkarni, et al. ∙ 0 ∙ share

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Training Probabilistic Spiking Neural Networks with First-to-spike Decoding

Third-generation neural networks, or Spiking Neural Networks (SNNs), aim...
10/29/2017 ∙ by Alireza Bagheri, et al. ∙ 0 ∙ share

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