3 papers
cs.LG2020
Towards Maximizing the Representation Gap between In-Domain & Out-of-Distribution Examples
Jay Nandy, Wynne Hsu, Mong Li Lee
Among existing uncertainty estimation approaches, Dirichlet Prior Network (DPN) distinctly models different predictive uncertainty types. However, for in-domain examples with high…
cs.CR2020
Approximate Manifold Defense Against Multiple Adversarial Perturbations
Jay Nandy, Wynne Hsu, Mong Li Lee
Existing defenses against adversarial attacks are typically tailored to a specific perturbation type. Using adversarial training to defend against multiple types of perturbation re…
cs.CV2018
Normal Similarity Network for Generative Modelling
Jay Nandy, Wynne Hsu, Mong Li Lee
Gaussian distributions are commonly used as a key building block in many generative models. However, their applicability has not been well explored in deep networks. In this paper,…