Proposal for a Leaky-Integrate-Fire Spiking Neuron based on Magneto-Electric Switching of Ferro-magnets. - Akhilesh Jaiswal 001; Sourjya Roy; Gopalakrishnan Srinivasan; Kaushik Roy 001 (CoRR, 2016)

Spike timing dependent plasticity based enhanced self-learning for efficient pattern recognition in spiking neural networks. - Gopalakrishnan Srinivasan; Sourjya Roy; Vijay Raghunathan; Kaushik Roy 001 (IJCNN, 2017)

Pruning Filters while Training for Efficiently Optimizing Deep Learning Networks. - Sourjya Roy; Priyadarshini Panda; Gopalakrishnan Srinivasan; Anand Raghunathan (IJCNN, 2020)

Gradual Channel Pruning While Training Using Feature Relevance Scores for Convolutional Neural Networks. - Sai Aparna Aketi; Sourjya Roy; Anand Raghunathan; Kaushik Roy 001 (IEEE Access, 2020)

Resistive Crossbars as Approximate Hardware Building Blocks for Machine Learning: Opportunities and Challenges. - Indranil Chakraborty; Mustafa Fayez Ali; Aayush Ankit; Shubham Jain; Sourjya Roy; Shrihari Sridharan; Amogh Agrawal; Anand Raghunathan; Kaushik Roy 001 (Proc. IEEE, 2020)

Design Tools for Resistive Crossbar based Machine Learning Accelerators. - Indranil Chakraborty; Sourjya Roy; Shrihari Sridharan; Mustafa Fayez Ali; Aayush Ankit; Shubham Jain; Anand Raghunathan (AICAS, 2021)

PIM-DRAM: Accelerating Machine Learning Workloads Using Processing in Commodity DRAM. - Sourjya Roy; Mustafa Fayez Ali; Anand Raghunathan (IEEE J. Emerg. Sel. Topics Circuits Syst., 2021)

TxSim: Modeling Training of Deep Neural Networks on Resistive Crossbar Systems. - Sourjya Roy; Shrihari Sridharan; Shubham Jain; Anand Raghunathan (IEEE Trans. Very Large Scale Integr. Syst., 2021)

Compute-in-Memory Technologies and Architectures for Deep Learning Workloads. - Mustafa Fayez Ali; Sourjya Roy; Utkarsh Saxena; Tanvi Sharma; Anand Raghunathan; Kaushik Roy 001 (IEEE Trans. Very Large Scale Integr. Syst., 2022)

Evaluation of STT-MRAM as a Scratchpad for Training in ML Accelerators. - Sourjya Roy; Cheng Wang 036; Anand Raghunathan (CoRR, 2023)