16 citations · 68 across the 10 of their papers we have counts for
5 papers · 1 filter
Pretraining ECG Data with Adversarial Masking Improves Model Generalizability for Data-Scarce Tasks
Jessica Y. Bo, Hen-Wei Huang, Alvin Chan +1
Medical datasets often face the problem of data scarcity, as ground truth labels must be generated by medical professionals. One mitigation strategy is to pretrain deep learning mo…
How Does Frequency Bias Affect the Robustness of Neural Image Classifiers against Common Corruption and Adversarial Perturbations?
Alvin Chan, Yew-Soon Ong, Clement Tan
Model robustness is vital for the reliable deployment of machine learning models in real-world applications. Recent studies have shown that data augmentation can result in model ov…
Deep Extrapolation for Attribute-Enhanced Generation
Alvin Chan, Ali Madani, Ben Krause +1
Attribute extrapolation in sample generation is challenging for deep neural networks operating beyond the training distribution. We formulate a new task for extrapolation in sequen…
What it Thinks is Important is Important: Robustness Transfers through Input Gradients
Alvin Chan, Yi Tay, Yew-Soon Ong
Adversarial perturbations are imperceptible changes to input pixels that can change the prediction of deep learning models. Learned weights of models robust to such perturbations a…
Metamorphic Relation Based Adversarial Attacks on Differentiable Neural Computer
Alvin Chan, Lei Ma, Felix Juefei-Xu +3
Deep neural networks (DNN), while becoming the driving force of many novel technology and achieving tremendous success in many cutting-edge applications, are still vulnerable to ad…