no code implementations • 1 Dec 2021 • Edward Kim, Jay Shenoy, Sebastian Junges, Daniel Fremont, Alberto Sangiovanni-Vincentelli, Sanjit Seshia
Simulation-based testing of autonomous vehicles (AVs) has become an essential complement to road testing to ensure safety.
no code implementations • 30 Nov 2020 • Jay Shenoy, Edward Kim, Xiangyu Yue, Taesung Park, Daniel Fremont, Alberto Sangiovanni-Vincentelli, Sanjit Seshia
In this paper, we present a platform to model dynamic and interactive scenarios, generate the scenarios in simulation with different modalities of labeled sensor data, and collect this information for data augmentation.
no code implementations • ICLR 2020 • Gil Lederman, Markus Rabe, Sanjit Seshia, Edward A. Lee
We demonstrate how to learn efficient heuristics for automated reasoning algorithms for quantified Boolean formulas through deep reinforcement learning.
no code implementations • 1 Dec 2019 • Edward Kim, Divya Gopinath, Corina Pasareanu, Sanjit Seshia
It is programmatic in that scenario representation is a program in a domain-specific probabilistic programming language which can be used to generate synthetic data to test a given perception module.
no code implementations • 2 Oct 2019 • Lakshya Jain, Wilson Wu, Steven Chen, Uyeong Jang, Varun Chandrasekaran, Sanjit Seshia, Somesh Jha
In this paper we explore semantic adversarial examples (SAEs) where an attacker creates perturbations in the semantic space representing the environment that produces input for the ML model.