activity
20212025
most citedDiverse Multimedia Layout Generation with Multi Choice Learning

12 citations · 25 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CR2025

What is the Cost of Differential Privacy for Deep Learning-Based Trajectory Generation?

Erik Buchholz, Natasha Fernandes, David D. Nguyen +3

While location trajectories offer valuable insights, they also reveal sensitive personal information. Differential Privacy (DP) offers formal protection, but achieving a favourable…

cs.LG2024

Contextual Chart Generation for Cyber Deception

David D. Nguyen, David Liebowitz, Surya Nepal +2

Honeyfiles are security assets designed to attract and detect intruders on compromised systems. Honeyfiles are a type of honeypot that mimic real, sensitive documents, creating the…

cs.LG2023★ 1 cited

Multiple Hypothesis Dropout: Estimating the Parameters of Multi-Modal Output Distributions

David D. Nguyen, David Liebowitz, Surya Nepal +1

In many real-world applications, from robotics to pedestrian trajectory prediction, there is a need to predict multiple real-valued outputs to represent several potential scenarios…

cs.CV2023★ 12 cited

Diverse Multimedia Layout Generation with Multi Choice Learning

David D. Nguyen, Surya Nepal, Salil S. Kanhere

Designing visually appealing layouts for multimedia documents containing text, graphs and images requires a form of creative intelligence. Modelling the generation of layouts has r…

cs.LG2023

Masked Vector Quantization

David D. Nguyen, David Leibowitz, Surya Nepal +1

Generative models with discrete latent representations have recently demonstrated an impressive ability to learn complex high-dimensional data distributions. However, their perform…

cs.CR2022★ 12 cited

Deception for Cyber Defence: Challenges and Opportunities

David Liebowitz, Surya Nepal, Kristen Moore +6

Deception is rapidly growing as an important tool for cyber defence, complementing existing perimeter security measures to rapidly detect breaches and data theft. One of the factor…

cs.CR2021

Is this IoT Device Likely to be Secure? Risk Score Prediction for IoT Devices Using Gradient Boosting Machines

Carlos A. Rivera Alvarez, Arash Shaghaghi, David D. Nguyen +1

Security risk assessment and prediction are critical for organisations deploying Internet of Things (IoT) devices. An absolute minimum requirement for enterprises is to verify the…