3 citations · 5 across the 4 of their papers we have counts for
4 papers
Unsupervised 3D Object Learning through Neuron Activity aware Plasticity
Beomseok Kang, Biswadeep Chakraborty, Saibal Mukhopadhyay
We present an unsupervised deep learning model for 3D object classification. Conventional Hebbian learning, a well-known unsupervised model, suffers from loss of local features lea…
An Algorithm-Hardware Co-design Framework to Overcome Imperfections of Mixed-signal DNN Accelerators
Payman Behnam, Uday Kamal, Saibal Mukhopadhyay
In recent years, processing in memory (PIM) based mixedsignal designs have been proposed as energy- and area-efficient solutions with ultra high throughput to accelerate DNN comput…
Learning Point Processes using Recurrent Graph Network
Saurabh Dash, Xueyuan She, Saibal Mukhopadhyay
We present a novel Recurrent Graph Network (RGN) approach for predicting discrete marked event sequences by learning the underlying complex stochastic process. Using the framework…
Unsupervised Hebbian Learning on Point Sets in StarCraft II
Beomseok Kang, Harshit Kumar, Saurabh Dash +1
Learning the evolution of real-time strategy (RTS) game is a challenging problem in artificial intelligent (AI) system. In this paper, we present a novel Hebbian learning method to…