Bipin Rajendran | DeepAI

AI Chat

Featured Co-authors

Osvaldo Simeone
158 publications
Symeon Chatzinotas
120 publications
Abu Sebastian
28 publications
Eva Lagunas
20 publications
Geethan Karunaratne
16 publications
Nicolas Skatchkovsky
14 publications
Alireza Bagheri
14 publications
Eleni Vasilaki
13 publications
Irem Boybat
12 publications
Evangelos Eleftheriou
12 publications
Jae-sun Seo
12 publications

∙ 08/22/2023

Energy-Efficient On-Board Radio Resource Management for Satellite Communications via Neuromorphic Computing

The latest satellite communication (SatCom) missions are characterized b...

0 Flor Ortiz, et al. ∙

∙ 04/21/2023

A Convolutional Spiking Network for Gesture Recognition in Brain-Computer Interfaces

Brain-computer interfaces are being explored for a wide variety of thera...

0 Yiming Ai, et al. ∙

∙ 02/02/2023

Bayesian Inference on Binary Spiking Networks Leveraging Nanoscale Device Stochasticity

Bayesian Neural Networks (BNNs) can overcome the problem of overconfiden...

0 Prabodh Katti, et al. ∙

∙ 11/02/2021

Spiking Generative Adversarial Networks With a Neural Network Discriminator: Local Training, Bayesian Models, and Continual Meta-Learning

Neuromorphic data carries information in spatio-temporal patterns encode...

0 Bleema Rosenfeld, et al. ∙

∙ 02/21/2021

Fast On-Device Adaptation for Spiking Neural Networks via Online-Within-Online Meta-Learning

Spiking Neural Networks (SNNs) have recently gained popularity as machin...

0 Bleema Rosenfeld, et al. ∙

∙ 02/10/2021

Hybrid In-memory Computing Architecture for the Training of Deep Neural Networks

The cost involved in training deep neural networks (DNNs) on von-Neumann...

0 Vinay Joshi, et al. ∙

∙ 08/05/2020

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

We discuss a high-performance and high-throughput hardware accelerator f...

0 Anakha V Babu, et al. ∙

∙ 04/30/2020

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 ...

24 Adnan Mehonic, et al. ∙

∙ 03/25/2020

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

Deep neural networks (DNNs) have surpassed human-level accuracy in a var...

0 Vinay Joshi, et al. ∙

∙ 05/28/2019

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

Spiking neural networks (SNN) are artificial computational models that h...

0 S. R. Nandakumar, et al. ∙

∙ 01/11/2019

Low-Power Neuromorphic Hardware for Signal Processing Applications

Machine learning has emerged as the dominant tool for implementing compl...

2 Bipin Rajendran, et al. ∙

∙ 10/23/2018

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

Spiking neural networks (SNNs) have garnered a great amount of interest ...

0 Navin Anwani, et al. ∙

∙ 10/23/2018

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

Artificial Neural Networks (ANNs) are currently being used as function a...

0 Bleema Rosenfeld, et al. ∙

∙ 02/22/2018

Adversarial Training for Probabilistic Spiking Neural Networks

Classifiers trained using conventional empirical risk minimization or ma...

0 Alireza Bagheri, et al. ∙

∙ 11/09/2017

Stochastic Deep Learning in Memristive Networks

We study the performance of stochastically trained deep neural networks ...

0 Anakha V Babu, et al. ∙

∙ 11/09/2017

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...

0 Shruti R. Kulkarni, et al. ∙

∙ 10/29/2017

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

Third-generation neural networks, or Spiking Neural Networks (SNNs), aim...

0 Alireza Bagheri, et al. ∙

Are you a researcher?
Expose your work
to one of the largest
A.I. communities in the world