3 papers
cs.LG2019
Enforcing Linearity in DNN succours Robustness and Adversarial Image Generation
Anindya Sarkar, Nikhil Kumar Gupta, Raghu Iyengar
Recent studies on the adversarial vulnerability of neural networks have shown that models trained with the objective of minimizing an upper bound on the worst-case loss over all po…
cs.LG2019
ODE guided Neural Data Augmentation Techniques for Time Series Data and its Benefits on Robustness
Anindya Sarkar, Anirudh Sunder Raj, Raghu Sesha Iyengar
Exploring adversarial attack vectors and studying their effects on machine learning algorithms has been of interest to researchers. Deep neural networks working with time series da…
cs.CV2019
MSG-GAN: Multi-Scale Gradients for Generative Adversarial Networks
Animesh Karnewar, Oliver Wang
While Generative Adversarial Networks (GANs) have seen huge successes in image synthesis tasks, they are notoriously difficult to adapt to different datasets, in part due to instab…