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08/11/2023
TrajPAC: Towards Robustness Verification of Pedestrian Trajectory Prediction Models
Robust pedestrian trajectory forecasting is crucial to developing safe a...
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02/10/2023
Incremental Satisfiability Modulo Theory for Verification of Deep Neural Networks
Constraint solving is an elementary way for verification of deep neural ...
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11/23/2022
Safety Analysis of Autonomous Driving Systems Based on Model Learning
We present a practical verification method for safety analysis of the au...
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07/18/2022
In-plane prestressed hair clip mechanism for the fastest untethered compliant fish robot
A trend has emerged over the past decades pointing to the harnessing of ...
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06/29/2022
In-plane prestressing: Inspiration from a hair clip
Structural instability is a hazard that leads to catastrophic failure an...
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06/01/2022
Defensive Design of Saturating Counters Based on Differential Privacy
The saturating counter is the basic module of the dynamic branch predict...
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01/23/2022
Weight Expansion: A New Perspective on Dropout and Generalization
While dropout is known to be a successful regularization technique, insi...
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06/05/2021
Ensemble Defense with Data Diversity: Weak Correlation Implies Strong Robustness
In this paper, we propose a framework of filter-based ensemble of deep n...
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01/25/2021
Probabilistic Robustness Analysis for DNNs based on PAC Learning
This paper proposes a black box based approach for analysing deep neural...
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10/15/2020
Improving Neural Network Verification through Spurious Region Guided Refinement
We propose a spurious region guided refinement approach for robustness v...
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08/27/2019
Asymptotically Optimal One- and Two-Sample Testing with Kernels
We characterize the asymptotic performance of nonparametric one- and two...
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02/26/2019
Analyzing Deep Neural Networks with Symbolic Propagation: Towards Higher Precision and Faster Verification
Deep neural networks (DNNs) have been shown lack of robustness for the v...
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02/21/2018
