Online and incremental machine learning approaches for IC yield improvement. - Hongge Chen; Duane S. Boning (ICCAD, 2017)

Efficient Spatial Variation Characterization via Matrix Completion. - Hongge Chen; Duane S. Boning; Zheng Zhang (CoRR, 2017)

Show-and-Fool: Crafting Adversarial Examples for Neural Image Captioning. - Hongge Chen; Huan Zhang 001; Pin-Yu Chen; Jinfeng Yi; Cho-Jui Hsieh (CoRR, 2017)

Attacking Visual Language Grounding with Adversarial Examples: A Case Study on Neural Image Captioning. - Hongge Chen; Huan Zhang 001; Pin-Yu Chen; Jinfeng Yi; Cho-Jui Hsieh (ACL (1), 2018)

Is Robustness the Cost of Accuracy? - A Comprehensive Study on the Robustness of 18 Deep Image Classification Models. - Dong Su; Huan Zhang 001; Hongge Chen; Jinfeng Yi; Pin-Yu Chen; Yupeng Gao (ECCV (12), 2018)

Towards Fast Computation of Certified Robustness for ReLU Networks. - Tsui-Wei Weng; Huan Zhang 001; Hongge Chen; Zhao Song 002; Cho-Jui Hsieh; Luca Daniel; Duane S. Boning; Inderjit S. Dhillon (ICML, 2018)

The Limitations of Adversarial Training and the Blind-Spot Attack. - Huan Zhang 001; Hongge Chen; Zhao Song 002; Duane S. Boning; Inderjit S. Dhillon; Cho-Jui Hsieh (ICLR (Poster), 2019)

Robust Decision Trees Against Adversarial Examples. - Hongge Chen; Huan Zhang 001; Duane S. Boning; Cho-Jui Hsieh (ICML, 2019)

Topology Attack and Defense for Graph Neural Networks: An Optimization Perspective. - Kaidi Xu; Hongge Chen; Sijia Liu 001; Pin-Yu Chen; Tsui-Wei Weng; Mingyi Hong 001; Xue Lin 001 (IJCAI, 2019)

Robustness Verification of Tree-based Models. - Hongge Chen; Huan Zhang 001; Si Si; Yang Li 058; Duane S. Boning; Cho-Jui Hsieh (NeurIPS, 2019)

Towards Stable and Efficient Training of Verifiably Robust Neural Networks. - Huan Zhang 001; Hongge Chen; Chaowei Xiao; Bo Li 026; Duane S. Boning; Cho-Jui Hsieh (CoRR, 2019)

Evading Real-Time Person Detectors by Adversarial T-shirt. - Kaidi Xu; Gaoyuan Zhang; Sijia Liu 001; Quanfu Fan; Mengshu Sun; Hongge Chen; Pin-Yu Chen; Yanzhi Wang; Xue Lin 001 (CoRR, 2019)

Adversarial T-Shirt! Evading Person Detectors in a Physical World. - Kaidi Xu; Gaoyuan Zhang; Sijia Liu 001; Quanfu Fan; Mengshu Sun; Hongge Chen; Pin-Yu Chen; Yanzhi Wang; Xue Lin 001 (ECCV (5), 2020)

Towards Stable and Efficient Training of Verifiably Robust Neural Networks. - Huan Zhang 001; Hongge Chen; Chaowei Xiao; Sven Gowal; Robert Stanforth; Bo Li 026; Duane S. Boning; Cho-Jui Hsieh (ICLR, 2020)

On Lp-norm Robustness of Ensemble Decision Stumps and Trees. - Yihan Wang; Huan Zhang 001; Hongge Chen; Duane S. Boning; Cho-Jui Hsieh (ICML, 2020)

Robust Deep Reinforcement Learning against Adversarial Perturbations on State Observations. - Huan Zhang 001; Hongge Chen; Chaowei Xiao; Bo Li 026; Mingyan Liu; Duane S. Boning; Cho-Jui Hsieh (NeurIPS, 2020)

Multi-Stage Influence Function. - Hongge Chen; Si Si; Yang Li 058; Ciprian Chelba; Sanjiv Kumar; Duane S. Boning; Cho-Jui Hsieh (NeurIPS, 2020)

Robust Deep Reinforcement Learning against Adversarial Perturbations on Observations. - Huan Zhang 001; Hongge Chen; Chaowei Xiao; Bo Li 026; Duane S. Boning; Cho-Jui Hsieh (CoRR, 2020)

On 𝓁p-norm Robustness of Ensemble Stumps and Trees. - Yihan Wang; Huan Zhang 001; Hongge Chen; Duane S. Boning; Cho-Jui Hsieh (CoRR, 2020)

Robust Reinforcement Learning on State Observations with Learned Optimal Adversary. - Huan Zhang 001; Hongge Chen; Duane S. Boning; Cho-Jui Hsieh (ICLR, 2021)

Hierarchical Model-Based Imitation Learning for Planning in Autonomous Driving. - Eli Bronstein; Mark Palatucci; Dominik Notz; Brandyn White; Alex Kuefler; Yiren Lu 001; Supratik Paul; Payam Nikdel; Paul Mougin; Hongge Chen; Justin Fu; Austin Abrams; et al. (IROS, 2022)

SHIFT3D: Synthesizing Hard Inputs For Tricking 3D Detectors. - Hongge Chen; Zhao Chen; Gregory P. Meyer; Dennis Park; Carl Vondrick; Ashish Shrivastava 001; Yuning Chai (ICCV, 2023)

Cohere3D: Exploiting Temporal Coherence for Unsupervised Representation Learning of Vision-based Autonomous Driving. - Yichen Xie 002; Hongge Chen; Gregory P. Meyer; Yong Jae Lee; Eric M. Wolff; Masayoshi Tomizuka; Wei Zhan; Yuning Chai; Xin Huang (CoRR, 2024)

DriveGPT: Scaling Autoregressive Behavior Models for Driving. - Xin Huang; Eric M. Wolff; Paul Vernaza; Tung Phan-Minh; Hongge Chen; David S. Hayden; Mark Edmonds; Brian Pierce; Xinxin Chen; Pratik Elias Jacob; Xiaobai Chen; Chingiz Tairbekov; et al. (CoRR, 2024)

Causal Composition Diffusion Model for Closed-loop Traffic Generation. - Haohong Lin; Xin Huang; Tung Phan-Minh; David S. Hayden; Huan Zhang 001; Ding Zhao; Siddhartha S. Srinivasa; Eric M. Wolff; Hongge Chen (CoRR, 2024)

Causal Composition Diffusion Model for Closed-loop Traffic Generation. - Haohong Lin; Xin Huang; Tung Phan; David S. Hayden; Huan Zhang 001; Ding Zhao; Siddhartha S. Srinivasa; Eric M. Wolff; Hongge Chen (CVPR, 2025)