45 citations · 80 across the 8 of their papers we have counts for
8 papers
DAS: A Deformable Attention to Capture Salient Information in CNNs
Farzad Salajegheh, Nader Asadi, Soroush Saryazdi +1
Convolutional Neural Networks (CNNs) excel in local spatial pattern recognition. For many vision tasks, such as object recognition and segmentation, salient information is also pre…
Prototype-Sample Relation Distillation: Towards Replay-Free Continual Learning
Nader Asadi, MohammadReza Davari, Sudhir Mudur +2
In Continual learning (CL) balancing effective adaptation while combating catastrophic forgetting is a central challenge. Many of the recent best-performing methods utilize various…
New Insights on Reducing Abrupt Representation Change in Online Continual Learning
Lucas Caccia, Rahaf Aljundi, Nader Asadi +3
In the online continual learning paradigm, agents must learn from a changing distribution while respecting memory and compute constraints. Experience Replay (ER), where a small sub…
Probing Representation Forgetting in Supervised and Unsupervised Continual Learning
MohammadReza Davari, Nader Asadi, Sudhir Mudur +2
Continual Learning research typically focuses on tackling the phenomenon of catastrophic forgetting in neural networks. Catastrophic forgetting is associated with an abrupt loss of…
Tackling Online One-Class Incremental Learning by Removing Negative Contrasts
Nader Asadi, Sudhir Mudur, Eugene Belilovsky
Recent work studies the supervised online continual learning setting where a learner receives a stream of data whose class distribution changes over time. Distinct from other conti…
New Insights on Reducing Abrupt Representation Change in Online Continual Learning
Lucas Caccia, Rahaf Aljundi, Nader Asadi +3
In the online continual learning paradigm, agents must learn from a changing distribution while respecting memory and compute constraints. Experience Replay (ER), where a small sub…
Towards Shape Biased Unsupervised Representation Learning for Domain Generalization
Nader Asadi, Amir M. Sarfi, Mehrdad Hosseinzadeh +2
It is known that, without awareness of the process, our brain appears to focus on the general shape of objects rather than superficial statistics of context. On the other hand, lea…
Diminishing the Effect of Adversarial Perturbations via Refining Feature Representation
Nader Asadi, AmirMohammad Sarfi, Mehrdad Hosseinzadeh +2
Deep neural networks are highly vulnerable to adversarial examples, which imposes severe security issues for these state-of-the-art models. Many defense methods have been proposed…