34 citations · 63 across the 3 of their papers we have counts for
8 papers
Scenic: A Language for Scenario Specification and Data Generation
Daniel J. Fremont, Edward Kim, Tommaso Dreossi +4
We propose a new probabilistic programming language for the design and analysis of cyber-physical systems, especially those based on machine learning. Specifically, we consider the…
A Formalization of Robustness for Deep Neural Networks
Tommaso Dreossi, Shromona Ghosh, Alberto Sangiovanni-Vincentelli +1
Deep neural networks have been shown to lack robustness to small input perturbations. The process of generating the perturbations that expose the lack of robustness of neural netwo…
VERIFAI: A Toolkit for the Design and Analysis of Artificial Intelligence-Based Systems
Tommaso Dreossi, Daniel J. Fremont, Shromona Ghosh +4
We present VERIFAI, a software toolkit for the formal design and analysis of systems that include artificial intelligence (AI) and machine learning (ML) components. VERIFAI particu…
A Minimum Discounted Reward Hamilton-Jacobi Formulation for Computing Reachable Sets
Anayo K. Akametalu, Shromona Ghosh, Jaime F. Fisac +1
We propose a novel formulation for approximating reachable sets through a minimum discounted reward optimal control problem. The formulation yields a continuous solution that can b…
Scenic: A Language for Scenario Specification and Scene Generation
Daniel J. Fremont, Tommaso Dreossi, Shromona Ghosh +3
We propose a new probabilistic programming language for the design and analysis of perception systems, especially those based on machine learning. Specifically, we consider the pro…
Counterexample-Guided Data Augmentation
Tommaso Dreossi, Shromona Ghosh, Xiangyu Yue +3
We present a novel framework for augmenting data sets for machine learning based on counterexamples. Counterexamples are misclassified examples that have important properties for r…