2 citations · 2 across the 13 of their papers we have counts for
4 papers · 1 filter
Learning Hyperspherical Time-Frequency Representations for Time-Series Out-of-Distribution Detection
Willian T. Lunardi, Samridha Shrestha, Martin Andreoni
Out-of-distribution (OOD) detection for time-series data remains comparatively underexplored compared to vision and language, with a limited principled understanding of how supervi…
RenderBender: A Survey on Adversarial Attacks Using Differentiable Rendering
Matthew Hull, Haoran Wang, Matthew Lau +8
Differentiable rendering techniques like Gaussian Splatting and Neural Radiance Fields have become powerful tools for generating high-fidelity models of 3D objects and scenes. Thei…
Non-Robust Features are Not Always Useful in One-Class Classification
Matthew Lau, Haoran Wang, Alec Helbling +5
The robustness of machine learning models has been questioned by the existence of adversarial examples. We examine the threat of adversarial examples in practical applications that…
ARCADE: Adversarially Regularized Convolutional Autoencoder for Network Anomaly Detection
Willian T. Lunardi, Martin Andreoni Lopez, Jean-Pierre Giacalone
As the number of heterogenous IP-connected devices and traffic volume increase, so does the potential for security breaches. The undetected exploitation of these breaches can bring…