3 papers
cs.LG2026
A New Technique for AI Explainability using Feature Association Map
Sayantani Ghosh, Amit Kumar Das, Amlan Chakrabarti
Lack of transparency in AI systems poses challenges in critical real-life applications. It is important to be able to explain the decisions of an AI system to ensure trust on the s…
cs.AI2026
PHISHREV: A Hybrid Machine Learning and Post-Hoc Non-monotonic Reasoning Framework for Context-Aware Phishing Website Classification
Mainak Sen, Kumar Sankar Ray, Amlan Chakrabarti
Phishing detection systems are predominantly rely on statistical machine learning models, which often lack contextual reasoning and are vulnerable to adversarial manipulation. In t…
quant-ph2026
Hybrid Coupling Topology with Dynamic ZZ Suppression for Optimizing Circuit Depth during Runtime in Superconducting Quantum Processor
Uday Sannigrahi, Amlan Chakrabarti, Swapnil Saha +1
To reduce circuit depth when executing Quantum algorithms, it is necessary to maximize qubit connectivity on a near-term quantum processor. While addressing this, we also need to e…