Pengfei Yang | DeepAI

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Featured Co-authors

Xi Chen
293 publications
Moshe Y. Vardi
92 publications
Jun Sun
89 publications
Liang Zhang
76 publications
Xiaowei Huang
61 publications
Hod Lipson
30 publications
Jingyi Wang
29 publications
Zhitang Chen
29 publications
Youcheng Sun
27 publications
Rui Hou
27 publications
Sven Schewe
25 publications

∙ 08/11/2023

TrajPAC: Towards Robustness Verification of Pedestrian Trajectory Prediction Models

Robust pedestrian trajectory forecasting is crucial to developing safe a...

0 Liang Zhang, et al. ∙

∙ 02/10/2023

Incremental Satisfiability Modulo Theory for Verification of Deep Neural Networks

Constraint solving is an elementary way for verification of deep neural ...

0 Pengfei Yang, et al. ∙

∙ 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...

0 Renjue Li, et al. ∙

∙ 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 ...

0 Zechen Xiong, et al. ∙

∙ 06/29/2022

In-plane prestressing: Inspiration from a hair clip

Structural instability is a hazard that leads to catastrophic failure an...

0 Zechen Xiong, et al. ∙

∙ 06/01/2022

Defensive Design of Saturating Counters Based on Differential Privacy

The saturating counter is the basic module of the dynamic branch predict...

0 Depeng Liu, et al. ∙

∙ 01/23/2022

Weight Expansion: A New Perspective on Dropout and Generalization

While dropout is known to be a successful regularization technique, insi...

0 Gaojie Jin, et al. ∙

∙ 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...

0 Renjue Li, et al. ∙

∙ 01/25/2021

Probabilistic Robustness Analysis for DNNs based on PAC Learning

This paper proposes a black box based approach for analysing deep neural...

3 Renjue Li, et al. ∙

∙ 10/15/2020

Improving Neural Network Verification through Spurious Region Guided Refinement

We propose a spurious region guided refinement approach for robustness v...

0 Pengfei Yang, et al. ∙

∙ 08/27/2019

Asymptotically Optimal One- and Two-Sample Testing with Kernels

We characterize the asymptotic performance of nonparametric one- and two...

0 Shengyu Zhu, et al. ∙

∙ 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...

0 Pengfei Yang, et al. ∙

∙ 02/21/2018

Universal Hypothesis Testing with Kernels: Asymptotically Optimal Tests for Goodness of Fit

We characterize the asymptotic performance of nonparametric goodness of ...

0 Shengyu Zhu, et al. ∙

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