activity
20212026
most citedTESDA: Transform Enabled Statistical Detection of Attacks in Deep Neural Networks

3 citations · 7 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CL2026★ 3 cited

Gemma 4 Technical Report

Gemma Team, Sherif El Abd, Vaibhav Aggarwal +320

We introduce Gemma 4, a new generation of open-weight, natively multimodal language models in the Gemma model family. Designed to advance compute efficiency and reasoning, the Gemm…

cs.RO2025

eCAV: An Edge-Assisted Evaluation Platform for Connected Autonomous Vehicles

Tyler Landle, Jordan Rapp, Dean Blank +4

As autonomous vehicles edge closer to widespread adoption, enhancing road safety through collision avoidance and minimization of collateral damage becomes imperative. Vehicle-to-ev…

cs.AI2024

RESOLVE: Relational Reasoning with Symbolic and Object-Level Features Using Vector Symbolic Processing

Mohamed Mejri, Chandramouli Amarnath, Abhijit Chatterjee

Modern transformer-based encoder-decoder architectures struggle with reasoning tasks due to their inability to effectively extract relational information between input objects (dat…

cs.AI2024

LARS-VSA: A Vector Symbolic Architecture For Learning with Abstract Rules

Mohamed Mejri, Chandramouli Amarnath, Abhijit Chatterjee

Human cognition excels at symbolic reasoning, deducing abstract rules from limited samples. This has been explained using symbolic and connectionist approaches, inspiring the devel…

cs.LG2024★ 1 cited

A Novel Hyperdimensional Computing Framework for Online Time Series Forecasting on the Edge

Mohamed Mejri, Chandramouli Amarnath, Abhijit Chatterjee

In recent years, both online and offline deep learning models have been developed for time series forecasting. However, offline deep forecasting models fail to adapt effectively to…

cs.CR2021★ 3 cited

TESDA: Transform Enabled Statistical Detection of Attacks in Deep Neural Networks

Chandramouli Amarnath, Aishwarya H. Balwani, Kwondo Ma +1

Deep neural networks (DNNs) are now the de facto choice for computer vision tasks such as image classification. However, their complexity and "black box" nature often renders the s…