3 citations · 3 across the 6 of their papers we have counts for
3 papers · 1 filter
ABS: Enforcing Constraint Satisfaction On Generated Sequences Via Automata-Guided Beam Search
Vincenzo Collura, Karim Tit, Laura Bussi +2
Sequence generation and prediction form a cornerstone of modern machine learning, with applications spanning natural language processing, program synthesis, and time-series forecas…
Deep generative models as an adversarial attack strategy for tabular machine learning
Salijona Dyrmishi, Mihaela Cătălina Stoian, Eleonora Giunchiglia +1
Deep Generative Models (DGMs) have found application in computer vision for generating adversarial examples to test the robustness of machine learning (ML) systems. Extending these…
How Realistic Is Your Synthetic Data? Constraining Deep Generative Models for Tabular Data
Mihaela Cătălina Stoian, Salijona Dyrmishi, Maxime Cordy +2
Deep Generative Models (DGMs) have been shown to be powerful tools for generating tabular data, as they have been increasingly able to capture the complex distributions that charac…