31 citations · 36 across the 8 of their papers we have counts for
12 papers
InForecaster: Forecasting Influenza Hemagglutinin Mutations Through the Lens of Anomaly Detection
Ali Garjani, Atoosa Malemir Chegini, Mohammadreza Salehi +6
The influenza virus hemagglutinin is an important part of the virus attachment to the host cells. The hemagglutinin proteins are one of the genetic regions of the virus with a high…
Your Out-of-Distribution Detection Method is Not Robust!
Mohammad Azizmalayeri, Arshia Soltani Moakhar, Arman Zarei +3
Out-of-distribution (OOD) detection has recently gained substantial attention due to the importance of identifying out-of-domain samples in reliability and safety. Although OOD det…
The Interplay between Distribution Parameters and the Accuracy-Robustness Tradeoff in Classification
Alireza Mousavi Hosseini, Amir Mohammad Abouei, Mohammad Hossein Rohban
Adversarial training tends to result in models that are less accurate on natural (unperturbed) examples compared to standard models. This can be attributed to either an algorithmic…
ZeroGrad : Mitigating and Explaining Catastrophic Overfitting in FGSM Adversarial Training
Zeinab Golgooni, Mehrdad Saberi, Masih Eskandar +1
Making deep neural networks robust to small adversarial noises has recently been sought in many applications. Adversarial training through iterative projected gradient descent (PGD…
Lagrangian Objective Function Leads to Improved Unforeseen Attack Generalization in Adversarial Training
Mohammad Azizmalayeri, Mohammad Hossein Rohban
Recent improvements in deep learning models and their practical applications have raised concerns about the robustness of these models against adversarial examples. Adversarial tra…
Dementia Severity Classification under Small Sample Size and Weak Supervision in Thick Slice MRI
Reza Shirkavand, Sana Ayromlou, Soroush Farghadani +7
Early detection of dementia through specific biomarkers in MR images plays a critical role in developing support strategies proactively. Fazekas scale facilitates an accurate quant…