Publications (6)
Anomaly detection using Diffusion-based methods
Aryan Bhosale, Samrat Mukherjee, Biplab Banerjee +1
This paper explores the utility of diffusion-based models for anomaly detection, focusing on their efficacy in identifying deviations in both compact and high-resolution datasets.…
Deep evolving semi-supervised anomaly detection
Jack Belham, Aryan Bhosale, Samrat Mukherjee +2
The aim of this paper is to formalise the task of continual semi-supervised anomaly detection (CSAD), with the aim of highlighting the importance of such a problem formulation whic…
Impact of Visual Context on Noisy Multimodal NMT: An Empirical Study for English to Indian Languages
Baban Gain, Dibyanayan Bandyopadhyay, Samrat Mukherjee +2
Neural Machine Translation (NMT) has made remarkable progress using large-scale textual data, but the potential of incorporating multimodal inputs, especially visual information, r…
Parameter-Efficient Continual Fine-Tuning: A Survey
Eric Nuertey Coleman, Luigi Quarantiello, Ziyue Liu +4
The emergence of large pre-trained networks has revolutionized the AI field, unlocking new possibilities and achieving unprecedented performance. However, these models inherit a fu…
Universal Adversarial Framework to Improve Adversarial Robustness for Diabetic Retinopathy Detection
Samrat Mukherjee, Dibyanayan Bandyopadhyay, Baban Gain +1
Diabetic Retinopathy (DR) is a prevalent illness associated with Diabetes which, if left untreated, can result in irreversible blindness. Deep Learning based systems are gradually…
GLAM: Efficient Continual Learning at Scale via Grouped LoRA Adapter Merging
Eric Nuertey Coleman, Irene Testa, Luigi Quarantiello +3
The ability to learn continuously over time remains a major challenge for modern machine learning systems, even in the era of Foundation Models. While the rich representations lear…