114 citations · 162 across the 5 of their papers we have counts for
5 papers
Inherent Weight Normalization in Stochastic Neural Networks
Georgios Detorakis, Sourav Dutta, Abhishek Khanna +3
Multiplicative stochasticity such as Dropout improves the robustness and generalizability of deep neural networks. Here, we further demonstrate that always-on multiplicative stocha…
Design space exploration of Ferroelectric FET based Processing-in-Memory DNN Accelerator
Insik Yoon, Matthew Jerry, Suman Datta +1
In this letter, we quantify the impact of device limitations on the classification accuracy of an artificial neural network, where the synaptic weights are implemented in a Ferroel…
Stochastic IMT (insulator-metal-transition) neurons: An interplay of thermal and threshold noise at bifurcation
Abhinav Parihar, Matthew Jerry, Suman Datta +1
Artificial neural networks can harness stochasticity in multiple ways to enable a vast class of computationally powerful models. Electronic implementation of such stochastic networ…
Vertex coloring of graphs via phase dynamics of coupled oscillatory networks
Abhinav Parihar, Nikhil Shukla, Matthew Jerry +2
While Boolean logic has been the backbone of digital information processing, there are classes of computationally hard problems wherein this conventional paradigm is fundamentally…
Computing with Dynamical Systems Based on Insulator-Metal-Transition Oscillators
Abhinav Parihar, Nikhil Shukla, Matthew Jerry +2
In this paper we review recent work on novel computing paradigms using coupled oscillatory dynamical systems. We explore systems of relaxation oscillators based on linear state tra…