5 citations · 6 across the 6 of their papers we have counts for
3 papers · 1 filter
Fine Tuning without Catastrophic Forgetting via Selective Low Rank Adaptation
Reza Akbarian Bafghi, Carden Bagwell, Avinash Ravichandran +2
Adapting deep learning models to new domains often requires computationally intensive retraining and risks catastrophic forgetting. While fine-tuning enables domain-specific adapta…
MixDiff: Mixing Natural and Synthetic Images for Robust Self-Supervised Representations
Reza Akbarian Bafghi, Nidhin Harilal, Claire Monteleoni +1
This paper introduces MixDiff, a new self-supervised learning (SSL) pre-training framework that combines real and synthetic images. Unlike traditional SSL methods that predominantl…
Parameter Efficient Fine-tuning of Self-supervised ViTs without Catastrophic Forgetting
Reza Akbarian Bafghi, Nidhin Harilal, Claire Monteleoni +1
Artificial neural networks often suffer from catastrophic forgetting, where learning new concepts leads to a complete loss of previously acquired knowledge. We observe that this is…