Maziar Raissi

Parameter Efficient Fine-tuning of Self-supervised ViTs without Catastrophic Forgetting

2024

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 issue is particularly magnified in vision transformers (ViTs), where post-pre-training …