activity
20172022
most citedDiscretization based Solutions for Secure Machine Learning against Adversarial Attacks

55 citations · 91 across the 7 of their papers we have counts for

collaborators

16 papers

gr-qc202215 cited

A simple analytic example of the gravitational wave memory effect

Indranil Chakraborty, Sayan Kar

We report an analytical example of the gravitational wave memory effect in exact plane wave spacetimes. A square pulse profile is chosen which gives rise to a curved wave region sa…

cs.LG20211 cited

Complexity-aware Adaptive Training and Inference for Edge-Cloud Distributed AI Systems

Yinghan Long, Indranil Chakraborty, Gopalakrishnan Srinivasan +1

The ubiquitous use of IoT and machine learning applications is creating large amounts of data that require accurate and real-time processing. Although edge-based smart data process…

cs.ET20217 cited

NAX: Co-Designing Neural Network and Hardware Architecture for Memristive Xbar based Computing Systems

Shubham Negi, Indranil Chakraborty, Aayush Ankit +1

In-Memory Computing (IMC) hardware using Memristive Crossbar Arrays (MCAs) are gaining popularity to accelerate Deep Neural Networks (DNNs) since it alleviates the "memory wall" pr…

cs.ET2020

On the Intrinsic Robustness of NVM Crossbars Against Adversarial Attacks

Deboleena Roy, Indranil Chakraborty, Timur Ibrayev +1

The increasing computational demand of Deep Learning has propelled research in special-purpose inference accelerators based on emerging non-volatile memory (NVM) technologies. Such…

cs.LG20206 cited

Conditionally Deep Hybrid Neural Networks Across Edge and Cloud

Yinghan Long, Indranil Chakraborty, Kaushik Roy

The pervasiveness of "Internet-of-Things" in our daily life has led to a recent surge in fog computing, encompassing a collaboration of cloud computing and edge intelligence. To th…

cs.ET2020

IMAC: In-memory multi-bit Multiplication andACcumulation in 6T SRAM Array

Mustafa Ali, Akhilesh Jaiswal, Sangamesh Kodge +3

`In-memory computing' is being widely explored as a novel computing paradigm to mitigate the well known memory bottleneck. This emerging paradigm aims at embedding some aspects of…