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cs.LG2025
Interpreting Adversarial Attacks and Defences using Architectures with Enhanced Interpretability
Akshay G Rao, Chandrashekhar Lakshminarayanan, Arun Rajkumar
Adversarial attacks in deep learning represent a significant threat to the integrity and reliability of machine learning models. Adversarial training has been a popular defence tec…
cs.LG2024
Closing the Gap in the Trade-off between Fair Representations and Accuracy
Biswajit Rout, Ananya B. Sai, Arun Rajkumar
The rapid developments of various machine learning models and their deployments in several applications has led to discussions around the importance of looking beyond the accuracie…