79 citations · 251 across the 17 of their papers we have counts for
19 papers
X-CHANGR: Changing Memristive Crossbar Mapping for Mitigating Line-Resistance Induced Accuracy Degradation in Deep Neural Networks
Amogh Agrawal, Chankyu Lee, Kaushik Roy
There is widespread interest in emerging technologies, especially resistive crossbars for accelerating Deep Neural Networks (DNNs). Resistive crossbars offer a highly-parallel and…
Non-equilibrium Green's Function and First Principle Approach to Modeling of Multiferroic Tunnel Junctions
Robert Andrawis, Kaushik Roy
Recently, multiferroic tunnel junctions (MFTJs) have gained significant spotlight in the literature due to its high tunneling electro-resistance together with its non-volatility. I…
PABO: Pseudo Agent-Based Multi-Objective Bayesian Hyperparameter Optimization for Efficient Neural Accelerator Design
Maryam Parsa, Aayush Ankit, Amirkoushyar Ziabari +1
The ever increasing computational cost of Deep Neural Networks (DNN) and the demand for energy efficient hardware for DNN acceleration has made accuracy and hardware cost co-optimi…
Reinforcement Learning with Low-Complexity Liquid State Machines
Wachirawit Ponghiran, Gopalakrishnan Srinivasan, Kaushik Roy
We propose reinforcement learning on simple networks consisting of random connections of spiking neurons (both recurrent and feed-forward) that can learn complex tasks with very li…
Synthesizing Images from Spatio-Temporal Representations using Spike-based Backpropagation
Deboleena Roy, Priyadarshini Panda, Kaushik Roy
Spiking neural networks (SNNs) offer a promising alternative to current artificial neural networks to enable low-power event-driven neuromorphic hardware. Spike-based neuromorphic…
Evaluating the Stability of Recurrent Neural Models during Training with Eigenvalue Spectra Analysis
Priyadarshini Panda, Efstathia Soufleri, Kaushik Roy
We analyze the stability of recurrent networks, specifically, reservoir computing models during training by evaluating the eigenvalue spectra of the reservoir dynamics. To circumve…