34 citations · 43 across the 6 of their papers we have counts for
6 papers
Do You Trust Your Model? Emerging Malware Threats in the Deep Learning Ecosystem
Dorjan Hitaj, Giulio Pagnotta, Fabio De Gaspari +4
Training high-quality deep learning models is a challenging task due to computational and technical requirements. A growing number of individuals, institutions, and companies incre…
PassGPT: Password Modeling and (Guided) Generation with Large Language Models
Javier Rando, Fernando Perez-Cruz, Briland Hitaj
Large language models (LLMs) successfully model natural language from vast amounts of text without the need for explicit supervision. In this paper, we investigate the efficacy of…
Forecasting Particle Accelerator Interruptions Using Logistic LASSO Regression
Sichen Li, Jochem Snuverink, Fernando Perez-Cruz +1
Unforeseen particle accelerator interruptions, also known as interlocks, lead to abrupt operational changes despite being necessary safety measures. These may result in substantial…
An evaluation of deep learning models for predicting water depth evolution in urban floods
Stefania Russo, Nathanaël Perraudin, Steven Stalder +4
In this technical report we compare different deep learning models for prediction of water depth rasters at high spatial resolution. Efficient, accurate, and fast methods for water…
Design Space Exploration and Explanation via Conditional Variational Autoencoders in Meta-model-based Conceptual Design of Pedestrian Bridges
Vera M. Balmer, Sophia V. Kuhn, Rafael Bischof +4
For conceptual design, engineers rely on conventional iterative (often manual) techniques. Emerging parametric models facilitate design space exploration based on quantifiable perf…
Vision Paper: Causal Inference for Interpretable and Robust Machine Learning in Mobility Analysis
Yanan Xin, Natasa Tagasovska, Fernando Perez-Cruz +1
Artificial intelligence (AI) is revolutionizing many areas of our lives, leading a new era of technological advancement. Particularly, the transportation sector would benefit from…