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2020 – today
- 2024
[j4]Xiaojun Jia
, Jianshu Li, Jindong Gu, Yang Bai, Xiaochun Cao:
Fast Propagation Is Better: Accelerating Single-Step Adversarial Training via Sampling Subnetworks. IEEE Trans. Inf. Forensics Secur. 19: 4547-4559 (2024)- [j3]Yuan Xun, Xiaojun Jia, Jindong Gu, Xinwei Liu, Qing Guo, Xiaochun Cao:
Minimalism is King! High-Frequency Energy-Based Screening for Data-Efficient Backdoor Attacks. IEEE Trans. Inf. Forensics Secur. 19: 4560-4571 (2024) - [j2]Xiaojun Jia, Yuefeng Chen, Xiaofeng Mao, Ranjie Duan, Jindong Gu, Rong Zhang, Hui Xue, Yang Liu, Xiaochun Cao:
Revisiting and Exploring Efficient Fast Adversarial Training via LAW: Lipschitz Regularization and Auto Weight Averaging. IEEE Trans. Inf. Forensics Secur. 19: 8125-8139 (2024) - [j1]Jindong Gu, Xiaojun Jia, Pau de Jorge, Wenqian Yu, Xinwei Liu, Avery Ma, Yuan Xun, Anjun Hu, Ashkan Khakzar, Zhijiang Li, Xiaochun Cao, Philip Torr:
A Survey on Transferability of Adversarial Examples Across Deep Neural Networks. Trans. Mach. Learn. Res. 2024 (2024) - [c30]Xuanlong Yu, Gianni Franchi, Jindong Gu, Emanuel Aldea:
Discretization-Induced Dirichlet Posterior for Robust Uncertainty Quantification on Regression. AAAI 2024: 6835-6843 - [c29]Haokun Chen, Yao Zhang, Denis Krompass, Jindong Gu, Volker Tresp:
FedDAT: An Approach for Foundation Model Finetuning in Multi-Modal Heterogeneous Federated Learning. AAAI 2024: 11285-11293 - [c28]Xinwei Liu, Xiaojun Jia, Jindong Gu, Yuan Xun, Siyuan Liang, Xiaochun Cao:
Does Few-Shot Learning Suffer from Backdoor Attacks? AAAI 2024: 19893-19901 - [c27]Hang Li, Chengzhi Shen, Philip Torr, Volker Tresp, Jindong Gu:
Self-Discovering Interpretable Diffusion Latent Directions for Responsible Text-to-Image Generation. CVPR 2024: 12006-12016 - [c26]Tianrui Lou, Xiaojun Jia, Jindong Gu, Li Liu, Siyuan Liang, Bangyan He, Xiaochun Cao:
Hide in Thicket: Generating Imperceptible and Rational Adversarial Perturbations on 3D Point Clouds. CVPR 2024: 24326-24335 - [c25]Andong Hua, Jindong Gu, Zhiyu Xue, Nicholas Carlini, Eric Wong, Yao Qin:
Initialization Matters for Adversarial Transfer Learning. CVPR 2024: 24831-24840 - [c24]Kuofeng Gao, Yang Bai, Jindong Gu, Shu-Tao Xia, Philip Torr, Zhifeng Li, Wei Liu:
Inducing High Energy-Latency of Large Vision-Language Models with Verbose Images. ICLR 2024 - [c23]Haoheng Lan, Jindong Gu, Philip Torr, Hengshuang Zhao:
Influencer Backdoor Attack on Semantic Segmentation. ICLR 2024 - [c22]Haochen Luo, Jindong Gu, Fengyuan Liu, Philip Torr:
An Image Is Worth 1000 Lies: Transferability of Adversarial Images across Prompts on Vision-Language Models. ICLR 2024 - [c21]Thomas Decker, Ananta R. Bhattarai, Jindong Gu, Volker Tresp, Florian Buettner:
Provably Better Explanations with Optimized Aggregation of Feature Attributions. ICML 2024 - [i73]Xinwei Liu, Xiaojun Jia, Jindong Gu, Yuan Xun, Siyuan Liang, Xiaochun Cao:
Does Few-shot Learning Suffer from Backdoor Attacks? CoRR abs/2401.01377 (2024) - [i72]Kuofeng Gao, Yang Bai, Jindong Gu, Shu-Tao Xia, Philip Torr, Zhifeng Li, Wei Liu:
Inducing High Energy-Latency of Large Vision-Language Models with Verbose Images. CoRR abs/2401.11170 (2024) - [i71]Zefeng Wang, Zhen Han, Shuo Chen, Fan Xue, Zifeng Ding, Xun Xiao, Volker Tresp, Philip Torr, Jindong Gu:
Stop Reasoning! When Multimodal LLMs with Chain-of-Thought Reasoning Meets Adversarial Images. CoRR abs/2402.14899 (2024) - [i70]Hao Cheng, Erjia Xiao, Jindong Gu, Le Yang, Jinhao Duan, Jize Zhang, Jiahang Cao, Kaidi Xu, Renjing Xu:
Unveiling Typographic Deceptions: Insights of the Typographic Vulnerability in Large Vision-Language Model. CoRR abs/2402.19150 (2024) - [i69]Tianrui Lou, Xiaojun Jia, Jindong Gu, Li Liu, Siyuan Liang, Bangyan He, Xiaochun Cao:
Hide in Thicket: Generating Imperceptible and Rational Adversarial Perturbations on 3D Point Clouds. CoRR abs/2403.05247 (2024) - [i68]Haochen Luo, Jindong Gu, Fengyuan Liu, Philip Torr:
An Image Is Worth 1000 Lies: Adversarial Transferability across Prompts on Vision-Language Models. CoRR abs/2403.09766 (2024) - [i67]Anjun Hu, Jindong Gu, Francesco Pinto, Konstantinos Kamnitsas, Philip Torr:
As Firm As Their Foundations: Can open-sourced foundation models be used to create adversarial examples for downstream tasks? CoRR abs/2403.12693 (2024) - [i66]Fengyuan Liu, Haochen Luo, Yiming Li, Philip Torr, Jindong Gu:
Model-agnostic Origin Attribution of Generated Images with Few-shot Examples. CoRR abs/2404.02697 (2024) - [i65]Shuo Chen, Zhen Han, Bailan He, Zifeng Ding, Wenqian Yu, Philip Torr, Volker Tresp, Jindong Gu:
Red Teaming GPT-4V: Are GPT-4V Safe Against Uni/Multi-Modal Jailbreak Attacks? CoRR abs/2404.03411 (2024) - [i64]Jindong Gu:
Responsible Generative AI: What to Generate and What Not. CoRR abs/2404.05783 (2024) - [i63]Runtao Liu, Ashkan Khakzar, Jindong Gu, Qifeng Chen, Philip Torr, Fabio Pizzati:
Latent Guard: a Safety Framework for Text-to-image Generation. CoRR abs/2404.08031 (2024) - [i62]Kuofeng Gao, Jindong Gu, Yang Bai, Shu-Tao Xia, Philip Torr, Wei Liu, Zhifeng Li:
Energy-Latency Manipulation of Multi-modal Large Language Models via Verbose Samples. CoRR abs/2404.16557 (2024) - [i61]Yang Bai, Ge Pei, Jindong Gu, Yong Yang, Xingjun Ma:
Special Characters Attack: Toward Scalable Training Data Extraction From Large Language Models. CoRR abs/2405.05990 (2024) - [i60]Xianzheng Ma, Yash Bhalgat, Brandon Smart, Shuai Chen, Xinghui Li, Jian Ding, Jindong Gu, Dave Zhenyu Chen, Songyou Peng, Jia-Wang Bian, Philip H. S. Torr, Marc Pollefeys, Matthias Nießner, Ian D. Reid, Angel X. Chang, Iro Laina, Victor Adrian Prisacariu:
When LLMs step into the 3D World: A Survey and Meta-Analysis of 3D Tasks via Multi-modal Large Language Models. CoRR abs/2405.10255 (2024) - [i59]Hao Cheng, Erjia Xiao, Jiahang Cao, Le Yang, Kaidi Xu, Jindong Gu, Renjing Xu:
Typography Leads Semantic Diversifying: Amplifying Adversarial Transferability across Multimodal Large Language Models. CoRR abs/2405.20090 (2024) - [i58]Xiaojun Jia, Tianyu Pang, Chao Du, Yihao Huang, Jindong Gu, Yang Liu, Xiaochun Cao, Min Lin:
Improved Techniques for Optimization-Based Jailbreaking on Large Language Models. CoRR abs/2405.21018 (2024) - [i57]Razieh Rezaei, Masoud Jalili Sabet, Jindong Gu, Daniel Rueckert, Philip Torr, Ashkan Khakzar:
Learning Visual Prompts for Guiding the Attention of Vision Transformers. CoRR abs/2406.03303 (2024) - [i56]Thomas Decker, Ananta R. Bhattarai, Jindong Gu, Volker Tresp, Florian Buettner:
Provably Better Explanations with Optimized Aggregation of Feature Attributions. CoRR abs/2406.05090 (2024) - [i55]Gengyuan Zhang, Mang Ling Ada Fok, Yan Xia, Yansong Tang, Daniel Cremers, Philip Torr, Volker Tresp, Jindong Gu:
Localizing Events in Videos with Multimodal Queries. CoRR abs/2406.10079 (2024) - [i54]Jinming Li, Yichen Zhu, Zhiyuan Xu, Jindong Gu, Minjie Zhu, Xin Liu, Ning Liu, Yaxin Peng, Feifei Feng, Jian Tang:
MMRo: Are Multimodal LLMs Eligible as the Brain for In-Home Robotics? CoRR abs/2406.19693 (2024) - [i53]Dai Liu, Jindong Gu, Hu Cao, Carsten Trinitis, Martin Schulz:
Dataset Distillation by Automatic Training Trajectories. CoRR abs/2407.14245 (2024) - [i52]Canyu Chen, Baixiang Huang, Zekun Li, Zhaorun Chen, Shiyang Lai, Xiongxiao Xu, Jia-Chen Gu, Jindong Gu, Huaxiu Yao, Chaowei Xiao, Xifeng Yan, William Yang Wang, Philip Torr, Dawn Song, Kai Shu:
Can Editing LLMs Inject Harm? CoRR abs/2407.20224 (2024) - [i51]Sensen Gao, Xiaojun Jia, Yihao Huang, Ranjie Duan, Jindong Gu, Yang Liu, Qing Guo:
RT-Attack: Jailbreaking Text-to-Image Models via Random Token. CoRR abs/2408.13896 (2024) - [i50]Hao Cheng, Erjia Xiao, Chengyuan Yu, Zhao Yao, Jiahang Cao, Qiang Zhang, Jiaxu Wang, Mengshu Sun, Kaidi Xu, Jindong Gu, Renjing Xu:
Manipulation Facing Threats: Evaluating Physical Vulnerabilities in End-to-End Vision Language Action Models. CoRR abs/2409.13174 (2024) - [i49]Tong Liu, Zhixin Lai, Gengyuan Zhang, Philip Torr, Vera Demberg, Volker Tresp, Jindong Gu:
Multimodal Pragmatic Jailbreak on Text-to-image Models. CoRR abs/2409.19149 (2024) - [i48]Haowei Zhang, Jianzhe Liu, Zhen Han, Shuo Chen, Bailan He, Volker Tresp, Zhiqiang Xu, Jindong Gu:
Visual Question Decomposition on Multimodal Large Language Models. CoRR abs/2409.19339 (2024) - 2023
- [c20]Zhen Han, Ruotong Liao, Jindong Gu, Yao Zhang, Zifeng Ding, Yujia Gu, Heinz Koeppl, Hinrich Schütze, Volker Tresp:
ECOLA: Enhancing Temporal Knowledge Embeddings with Contextualized Language Representations. ACL (Findings) 2023: 5433-5447 - [c19]Jindong Gu, Fangyun Wei, Philip H. S. Torr, Han Hu:
Exploring Non-additive Randomness on ViT against Query-Based Black-Box Attacks. BMVC 2023: 406-408 - [c18]Kuofeng Gao, Yang Bai, Jindong Gu, Yong Yang, Shu-Tao Xia:
Backdoor Defense via Adaptively Splitting Poisoned Dataset. CVPR 2023: 4005-4014 - [c17]Hang Li, Jindong Gu, Rajat Koner, Sahand Sharifzadeh, Volker Tresp:
Do DALL-E and Flamingo Understand Each Other? ICCV 2023: 1999-2010 - [c16]Haokun Chen, Ahmed Frikha, Denis Krompass, Jindong Gu, Volker Tresp:
FRAug: Tackling Federated Learning with Non-IID Features via Representation Augmentation. ICCV 2023: 4826-4836 - [c15]Gengyuan Zhang, Jisen Ren, Jindong Gu, Volker Tresp:
Multi-event Video-Text Retrieval. ICCV 2023: 22056-22066 - [c14]Shuo Chen, Jindong Gu, Zhen Han, Yunpu Ma, Philip H. S. Torr, Volker Tresp:
Benchmarking Robustness of Adaptation Methods on Pre-trained Vision-Language Models. NeurIPS 2023 - [i47]Jindong Gu:
Explainability and Robustness of Deep Visual Classification Models. CoRR abs/2301.01343 (2023) - [i46]Haoheng Lan, Jindong Gu, Philip H. S. Torr, Hengshuang Zhao:
Influencer Backdoor Attack on Semantic Segmentation. CoRR abs/2303.12054 (2023) - [i45]Kuofeng Gao, Yang Bai, Jindong Gu, Yong Yang, Shu-Tao Xia:
Backdoor Defense via Adaptively Splitting Poisoned Dataset. CoRR abs/2303.12993 (2023) - [i44]Jindong Gu, Ahmad Beirami, Xuezhi Wang, Alex Beutel, Philip H. S. Torr, Yao Qin:
Towards Robust Prompts on Vision-Language Models. CoRR abs/2304.08479 (2023) - [i43]Shuo Chen, Jindong Gu, Zhen Han, Yunpu Ma, Philip H. S. Torr, Volker Tresp:
Benchmarking Robustness of Adaptation Methods on Pre-trained Vision-Language Models. CoRR abs/2306.02080 (2023) - [i42]Wenqian Yu, Jindong Gu, Zhijiang Li, Philip H. S. Torr:
Reliable Evaluation of Adversarial Transferability. CoRR abs/2306.08565 (2023) - [i41]Jindong Gu, Zhen Han, Shuo Chen, Ahmad Beirami, Bailan He, Gengyuan Zhang, Ruotong Liao, Yao Qin, Volker Tresp, Philip H. S. Torr:
A Systematic Survey of Prompt Engineering on Vision-Language Foundation Models. CoRR abs/2307.12980 (2023) - [i40]Haokun Chen, Denis Krompass, Jindong Gu, Volker Tresp:
FedPop: Federated Population-based Hyperparameter Tuning. CoRR abs/2308.08634 (2023) - [i39]Xuanlong Yu, Gianni Franchi, Jindong Gu, Emanuel Aldea:
Discretization-Induced Dirichlet Posterior for Robust Uncertainty Quantification on Regression. CoRR abs/2308.09065 (2023) - [i38]Xiaojun Jia, Yuefeng Chen, Xiaofeng Mao, Ranjie Duan, Jindong Gu, Rong Zhang, Hui Xue, Xiaochun Cao:
Revisiting and Exploring Efficient Fast Adversarial Training via LAW: Lipschitz Regularization and Auto Weight Averaging. CoRR abs/2308.11443 (2023) - [i37]Gengyuan Zhang, Jisen Ren, Jindong Gu, Volker Tresp:
Multi-event Video-Text Retrieval. CoRR abs/2308.11551 (2023) - [i36]Haokun Chen, Yao Zhang, Denis Krompass, Jindong Gu, Volker Tresp:
FedDAT: An Approach for Foundation Model Finetuning in Multi-Modal Heterogeneous Federated Learning. CoRR abs/2308.12305 (2023) - [i35]Jindong Gu, Fangyun Wei, Philip H. S. Torr, Han Hu:
Exploring Non-additive Randomness on ViT against Query-Based Black-Box Attacks. CoRR abs/2309.06438 (2023) - [i34]Zhihao Hu, Yiran Xu, Mengnan Du, Jindong Gu, Xinmei Tian, Fengxiang He:
Boosting Fair Classifier Generalization through Adaptive Priority Reweighing. CoRR abs/2309.08375 (2023) - [i33]Xiaojun Jia, Jianshu Li, Jindong Gu, Yang Bai, Xiaochun Cao:
Fast Propagation is Better: Accelerating Single-Step Adversarial Training via Sampling Subnetworks. CoRR abs/2310.15444 (2023) - [i32]Jindong Gu, Xiaojun Jia, Pau de Jorge, Wenqian Yu, Xinwei Liu, Avery Ma, Yuan Xun, Anjun Hu, Ashkan Khakzar, Zhijiang Li, Xiaochun Cao, Philip H. S. Torr:
A Survey on Transferability of Adversarial Examples across Deep Neural Networks. CoRR abs/2310.17626 (2023) - [i31]Gengyuan Zhang, Jinhe Bi, Jindong Gu, Volker Tresp:
SPOT! Revisiting Video-Language Models for Event Understanding. CoRR abs/2311.12919 (2023) - [i30]Shitong Sun, Jindong Gu, Shaogang Gong:
Benchmarking Robustness of Text-Image Composed Retrieval. CoRR abs/2311.14837 (2023) - [i29]Hang Li, Chengzhi Shen, Philip H. S. Torr, Volker Tresp, Jindong Gu:
Self-Discovering Interpretable Diffusion Latent Directions for Responsible Text-to-Image Generation. CoRR abs/2311.17216 (2023) - [i28]Shuo Chen, Zhen Han, Bailan He, Mark Buckley, Philip H. S. Torr, Volker Tresp, Jindong Gu:
Understanding and Improving In-Context Learning on Vision-language Models. CoRR abs/2311.18021 (2023) - [i27]Avery Ma, Amir-massoud Farahmand, Yangchen Pan, Philip H. S. Torr, Jindong Gu:
Improving Adversarial Transferability via Model Alignment. CoRR abs/2311.18495 (2023) - [i26]Xiaojun Jia, Jindong Gu, Yihao Huang, Simeng Qin, Qing Guo, Yang Liu, Xiaochun Cao:
TranSegPGD: Improving Transferability of Adversarial Examples on Semantic Segmentation. CoRR abs/2312.02207 (2023) - [i25]Dongchen Han, Xiaojun Jia, Yang Bai, Jindong Gu, Yang Liu, Xiaochun Cao:
OT-Attack: Enhancing Adversarial Transferability of Vision-Language Models via Optimal Transport Optimization. CoRR abs/2312.04403 (2023) - [i24]Andong Hua, Jindong Gu, Zhiyu Xue, Nicholas Carlini, Eric Wong, Yao Qin:
Initialization Matters for Adversarial Transfer Learning. CoRR abs/2312.05716 (2023) - [i23]Xingqiao Li, Jindong Gu, Zhiyong Wang, Yancheng Yuan, Bo Du, Fengxiang He:
XAI for In-hospital Mortality Prediction via Multimodal ICU Data. CoRR abs/2312.17624 (2023) - 2022
- [b1]Jindong Gu:
Explainability and robustness of deep visual classification models. Ludwig Maximilian University of Munich, Germany, 2022 - [c13]Xinwei Liu, Jian Liu, Yang Bai, Jindong Gu, Tao Chen, Xiaojun Jia, Xiaochun Cao:
Watermark Vaccine: Adversarial Attacks to Prevent Watermark Removal. ECCV (14) 2022: 1-17 - [c12]Boxi Wu, Jindong Gu, Zhifeng Li, Deng Cai, Xiaofei He, Wei Liu:
Towards Efficient Adversarial Training on Vision Transformers. ECCV (13) 2022: 307-325 - [c11]Jindong Gu, Hengshuang Zhao, Volker Tresp, Philip H. S. Torr:
SegPGD: An Effective and Efficient Adversarial Attack for Evaluating and Boosting Segmentation Robustness. ECCV (29) 2022: 308-325 - [c10]Jindong Gu, Volker Tresp, Yao Qin:
Are Vision Transformers Robust to Patch Perturbations? ECCV (12) 2022: 404-421 - [i22]Xinwei Liu, Jian Liu, Yang Bai, Jindong Gu, Tao Chen, Xiaojun Jia, Xiaochun Cao:
Watermark Vaccine: Adversarial Attacks to Prevent Watermark Removal. CoRR abs/2207.08178 (2022) - [i21]Boxi Wu, Jindong Gu, Zhifeng Li, Deng Cai, Xiaofei He, Wei Liu:
Towards Efficient Adversarial Training on Vision Transformers. CoRR abs/2207.10498 (2022) - [i20]Jindong Gu, Hengshuang Zhao, Volker Tresp, Philip H. S. Torr:
SegPGD: An Effective and Efficient Adversarial Attack for Evaluating and Boosting Segmentation Robustness. CoRR abs/2207.12391 (2022) - [i19]Yao Zhang, Haokun Chen, Ahmed Frikha, Yezi Yang, Denis Krompass, Gengyuan Zhang, Jindong Gu, Volker Tresp:
CL-CrossVQA: A Continual Learning Benchmark for Cross-Domain Visual Question Answering. CoRR abs/2211.10567 (2022) - [i18]Hang Li, Jindong Gu, Rajat Koner, Sahand Sharifzadeh, Volker Tresp:
Do DALL-E and Flamingo Understand Each Other? CoRR abs/2212.12249 (2022) - 2021
- [c9]Jindong Gu:
Interpretable Graph Capsule Networks for Object Recognition. AAAI 2021: 1469-1477 - [c8]Jindong Gu, Volker Tresp, Han Hu:
Capsule Network Is Not More Robust Than Convolutional Network. CVPR 2021: 14309-14317 - [c7]Zhiliang Wu, Yinchong Yang, Jindong Gu, Volker Tresp:
Quantifying Predictive Uncertainty in Medical Image Analysis with Deep Kernel Learning. ICHI 2021: 63-72 - [c6]Jindong Gu, Baoyuan Wu, Volker Tresp:
Effective and Efficient Vote Attack on Capsule Networks. ICLR 2021 - [c5]Jindong Gu, Rui Zhao, Volker Tresp:
Semantics for Global and Local Interpretation of Deep Convolutional Neural Networks. IJCNN 2021: 1-8 - [i17]Jindong Gu, Baoyuan Wu, Volker Tresp:
Effective and Efficient Vote Attack on Capsule Networks. CoRR abs/2102.10055 (2021) - [i16]Jindong Gu, Volker Tresp, Han Hu:
Capsule Network is Not More Robust than Convolutional Network. CoRR abs/2103.15459 (2021) - [i15]Zhiliang Wu, Yinchong Yang, Jindong Gu, Volker Tresp:
Quantifying Predictive Uncertainty in Medical Image Analysis with Deep Kernel Learning. CoRR abs/2106.00638 (2021) - [i14]Boxi Wu, Heng Pan, Li Shen, Jindong Gu, Shuai Zhao, Zhifeng Li, Deng Cai, Xiaofei He, Wei Liu:
Attacking Adversarial Attacks as A Defense. CoRR abs/2106.04938 (2021) - [i13]Jindong Gu, Wei Liu, Yonglong Tian:
Simple Distillation Baselines for Improving Small Self-supervised Models. CoRR abs/2106.11304 (2021) - [i12]Jindong Gu, Volker Tresp, Yao Qin:
Are Vision Transformers Robust to Patch Perturbations? CoRR abs/2111.10659 (2021) - [i11]Jindong Gu, Hengshuang Zhao, Volker Tresp, Philip H. S. Torr:
Adversarial Examples on Segmentation Models Can be Easy to Transfer. CoRR abs/2111.11368 (2021) - 2020
- [c4]Jindong Gu, Zhiliang Wu, Volker Tresp:
Introspective Learning by Distilling Knowledge from Online Self-explanation. ACCV (4) 2020: 36-52 - [c3]Jindong Gu, Volker Tresp:
Improving the Robustness of Capsule Networks to Image Affine Transformations. CVPR 2020: 7283-7291 - [c2]Jindong Gu, Volker Tresp:
Search for Better Students to Learn Distilled Knowledge. ECAI 2020: 1159-1165 - [i10]Jindong Gu, Volker Tresp:
Search for Better Students to Learn Distilled Knowledge. CoRR abs/2001.11612 (2020) - [i9]Jindong Gu, Zhiliang Wu, Volker Tresp:
Introspective Learning by Distilling Knowledge from Online Self-explanation. CoRR abs/2009.09140 (2020) - [i8]Jindong Gu, Volker Tresp:
Interpretable Graph Capsule Networks for Object Recognition. CoRR abs/2012.01674 (2020)
2010 – 2019
- 2019
- [i7]Jindong Gu, Volker Tresp:
Saliency Methods for Explaining Adversarial Attacks. CoRR abs/1908.08413 (2019) - [i6]Jindong Gu, Daniela Oelke:
Understanding Bias in Machine Learning. CoRR abs/1909.01866 (2019) - [i5]Jindong Gu, Volker Tresp:
Semantics for Global and Local Interpretation of Deep Neural Networks. CoRR abs/1910.09085 (2019) - [i4]Jindong Gu, Volker Tresp:
Contextual Prediction Difference Analysis. CoRR abs/1910.09086 (2019) - [i3]Jindong Gu, Volker Tresp:
Improving the Robustness of Capsule Networks to Image Affine Transformations. CoRR abs/1911.07968 (2019) - [i2]Jindong Gu, Volker Tresp:
Neural Network Memorization Dissection. CoRR abs/1911.09537 (2019) - 2018
- [c1]Jindong Gu, Yinchong Yang, Volker Tresp:
Understanding Individual Decisions of CNNs via Contrastive Backpropagation. ACCV (3) 2018: 119-134 - [i1]Jindong Gu, Yinchong Yang, Volker Tresp:
Understanding Individual Decisions of CNNs via Contrastive Backpropagation. CoRR abs/1812.02100 (2018)
Coauthor Index
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