Stochastic deep learning in memristive networks. - Anakha V. Babu; Bipin Rajendran (ICECS, 2017)

Spiking neural networks - Algorithms, hardware implementations and applications. - Shruti R. Kulkarni; Anakha V. Babu; Bipin Rajendran (MWSCAS, 2017)

Acceleration of Convolutional Networks Using Nanoscale Memristive Devices. - Shruti R. Kulkarni; Anakha V. Babu; Bipin Rajendran (EANN, 2018)

Stochastic learning in deep neural networks based on nanoscale PCMO device characteristics. - Anakha V. Babu; Sandip Lashkare; Udayan Ganguly; Bipin Rajendran (Neurocomputing, 2018)

SpinAPS: A High-Performance Spintronic Accelerator for Probabilistic Spiking Neural Networks. - Anakha V. Babu; Osvaldo Simeone; Bipin Rajendran (CoRR, 2020)

Deep learning at the edge enables real-time streaming ptychographic imaging. - Anakha V. Babu; Tao Zhou; Saugat Kandel; Tekin Bicer; Zhengchun Liu; William Judge; Daniel J. Ching; Yi Jiang; Sinisa Veseli; Steven Henke; Ryan Chard; Yudong Yao; et al. (CoRR, 2022)

AI-assisted automated workflow for real-time x-ray ptychography data analysis via federated resources. - Anakha V. Babu; Tekin Bicer; Saugat Kandel; Tao Zhou; Daniel J. Ching; Steven Henke; Sinisa Veseli; Ryan Chard; Antonino Miceli; Mathew Joseph Cherukara (High Performance Computing for Imaging, 2023)