Publications

Our publications provide insight into some of our leading-edge research.

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2023

Interpretable Trajectory Prediction for Autonomous Vehicles via Counterfactual Responsibility
Kai-Chieh Hsu, Karen Leung, Yuxiao Chen, Jaime Fernandez Fisac, Marco Pavone
Task-Aware Risk Estimation of Perception Failures for Autonomous Vehicles
Pasquale Antonante, Sushant Veer, Karen Leung, Xinshuo Weng, Luca Carlone, Marco Pavone
Object Pose Estimation with Statistical Guarantees: Conformal Keypoint Detection and Geometric Uncertainty Propagation
Heng Yang, Marco Pavone
Selected as a Highlight Paper
Learning Autonomous Vehicle Safety Concepts from Demonstrations
Karen Leung, Sushant Veer, Edward Schmerling, Marco Pavone

2022

Task-Relevant Failure Detection for Trajectory Predictors in Autonomous Vehicles
Alec Farid, Sushant Veer, Boris Ivanovic, Karen Leung, Marco Pavone
Robust Trajectory Prediction against Adversarial Attacks
Yulong Cao, Danfei Xu, Xinshuo Weng, Z. Morely Mao, Anima Anandkumar, Chaowei Xiao, Marco Pavone
Selected for Oral Presentation

2021

Optimizing Selective Protection for CNN Resilience
Abdulrahman Mahmoud, Siva Hari, Christopher W. Fletcher, Sarita V. Adve, Charbel Sakr, Naresh Shanbhag, Pavlo Molchanov, Michael B. Sullivan, Timothy Tsai, Steve Keckler
Generating and Characterizing Scenarios for Safety Testing of Autonomous Vehicles
Zahra Ghodsi, Siva Hari, Iuri Frosio, Timothy Tsai, Alejandro Troccoli, Steve Keckler, Siddharth Garg, Anima Anandkumar
Making Convolutions Resilient via Algorithm-Based Error Detection Techniques
Siva Hari, Michael B. Sullivan, Timothy Tsai, Steve Keckler

2020

Generating and Characterizing Scenarios for Safety Testing of Autonomous Vehicles
Zahra Ghodsi, Siva Hari, Iuri Frosio, Timothy Tsai, Alejandro Troccoli, Steve Keckler, Siddharth Garg, Anima Anandkumar
Generating and Characterizing Scenarios for Safety Testing of Autonomous Vehicles
Zahra Ghodsi, Siva Hari, Iuri Frosio, Timothy Tsai, Alejandro Troccoli, Steve Keckler, Siddharth Garg, Anima Anandkumar
HarDNN: Fine-Grained Vulnerability Evaluation and Protection for Convolutional Neural Networks
Abdulrahman Mahmoud, Siva Hari, Christopher W. Fletcher, Sarita V. Adve, Charbel Sakr, Naresh Shanbhag, Pavlo Molchanov, Michael B. Sullivan, Timothy Tsai, Steve Keckler
ML-driven Malware that Targets AV Safety
Saurabh Jha, Shengkun Cui, Subho S. Banerjee, James Cyriac, Timothy Tsai, Zbigniew T. Kalbarczyk, Ravishankar K. Iyer
PyTorchFI: A Runtime Perturbation Tool for DNNs
Abdulrahman Mahmoud, Neeraj Aggarwal, Alex Nobbe, Jose Rodrigo Sanchez Vicarte, Sarita V. Adve, Christopher W. Fletcher, Iuri Frosio, Siva Hari
Making Convolutions Resilient via Algorithm-Based Error Detection Techniques
Siva Hari, Michael B. Sullivan, Timothy Tsai, Steve Keckler
ML-driven Malware that Targets AV Safety
Saurabh Jha, Shengkun Cui, Subho S. Banerjee, James Cyriac, Timothy Tsai, Zbigniew T. Kalbarczyk, Ravishankar K. Iyer
HarDNN: Feature Map Vulnerability Evaluation in CNNs
Abdulrahman Mahmoud, Siva Hari, Christopher W. Fletcher, Sarita V. Adve, Charbel Sakr, Naresh Shanbhag, Pavlo Molchanov, Michael B. Sullivan, Timothy Tsai, Steve Keckler

2019

ML-based Fault Injection for Autonomous Vehicles: A Case for Bayesian Fault Injection
Saurabh Jha, Subho S. Banerjee, Timothy Tsai, Siva Hari, Michael B. Sullivan, Zbigniew T. Kalbarczyk, Steve Keckler, Ravishankar K. Iyer
ML-based Fault Injection for Autonomous Vehicles: A Case for Bayesian Fault Injection
Saurabh Jha, Subho Banerjee, Timothy Tsai, Siva Hari, Michael B. Sullivan, Zbigniew T. Kalbarczyk, Steve Keckler, Ravishankar K. Iyer

2017

Understanding Error Propagation in Deep Learning Neural Network (DNN) Accelerators and Applications
Guanpeng Li, Siva Hari, Michael B. Sullivan, Timothy Tsai, Karthik Pattabiraman, Joel Emer, Steve Keckler