activity
20162021
most citedReaction-Drift Model for Switching Transients in PrCaMnO-Based Resistive RAM

16 citations · 17 across the 9 of their papers we have counts for

collaborators

20 papers

cs.ET2021

Stochasticity Invariance Control in PrCaMnO RRAM to enable Large-Scale Stochastic Recurrent Neural Networks

Vivek Saraswat, Udayan Ganguly

Emerging non-volatile memories have been proposed for a wide range of applications from easing the von-Neumann bottleneck to neuromorphic applications. Specifically, scalable RRAMs…

cs.ET20211 cited

Exploiting the Electrothermal Timescale in PrMnO3 RRAM for a compact, clock-less neuron exhibiting biological spiking patterns

Omkar Phadke, Jayatika Sakhuja, Vivek Saraswat +1

Spiking Neural Networks (SNNs) are gaining widespread momentum in the field of neuromorphic computing. These network systems integrated with neurons and synapses provide computatio…

cs.NE2021

Algorithm For 3D-Chemotaxis Using Spiking Neural Network

Jayesh Choudhary, Vivek Saraswat, Udayan Ganguly

In this work, we aim to devise an end-to-end spiking implementation for contour tracking in 3D media inspired by chemotaxis, where the worm reaches the region which has the given s…

cs.NE2021

Spiking-GAN: A Spiking Generative Adversarial Network Using Time-To-First-Spike Coding

Vineet Kotariya, Udayan Ganguly

Spiking Neural Networks (SNNs) have shown great potential in solving deep learning problems in an energy-efficient manner. However, they are still limited to simple classification…

q-bio.NC2021

Simplified Klinokinesis using Spiking Neural Networks for Resource-Constrained Navigation on the Neuromorphic Processor Loihi

Apoorv Kishore, Vivek Saraswat, Udayan Ganguly

C. elegans shows chemotaxis using klinokinesis where the worm senses the concentration based on a single concentration sensor to compute the concentration gradient to perform forag…

eess.AS2021

Hardware-Friendly Synaptic Orders and Timescales in Liquid State Machines for Speech Classification

Vivek Saraswat, Ajinkya Gorad, Anand Naik +2

Liquid State Machines are brain inspired spiking neural networks (SNNs) with random reservoir connectivity and bio-mimetic neuronal and synaptic models. Reservoir computing network…