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Viewing Publication 1 - 100 from 225

2024

Exploring Channel-Aware Typical Features for Out-of-Distribution DetectionRundong He, Yue Yuan, Zhongyi Han, Fan Wang, Wan Su, Yilong Yin, Tongliang Liu, Yongshun Gong. AAAI 2024: 12402-12410 [doi]

E2HQV: High-Quality Video Generation from Event Camera via Theory-Inspired Model-Aided Deep LearningQiang Qu, Yiran Shen 0001, Xiaoming Chen 0006, Yuk Ying Chung, Tongliang Liu. AAAI 2024: 4632-4640 [doi]

ProtoSimi: label correction for fine-grained visual categorizationJialiang Shen, Yu Yao, Shaoli Huang, Zhiyong Wang, Jing Zhang, Ruxing Wang, Jun Yu, Tongliang Liu. ml, 113(4):1903-1920, April 2024. [doi]

Conditional Consistency Regularization for Semi-Supervised Multi-Label Image ClassificationZhengning Wu, Tianyu He, Xiaobo Xia, Jun Yu 0001, Xu Shen, Tongliang Liu. tmm, 26:4206-4216, 2024. [doi]

Regularly Truncated M-Estimators for Learning With Noisy LabelsXiaobo Xia, Pengqian Lu, Chen Gong 0002, Bo Han 0003, Jun Yu 0001, Jun Yu 0002, Tongliang Liu. pami, 46(5):3522-3536, May 2024. [doi]

Quantization Aware Attack: Enhancing Transferable Adversarial Attacks by Model QuantizationYulong Yang, Chenhao Lin, Qian Li, Zhengyu Zhao 0001, Haoran Fan, Dawei Zhou, Nannan Wang 0001, Tongliang Liu, Chao Shen 0001. tifs, 19:3265-3278, 2024. [doi]

2023

Relation-Aware Fine-Grained Reasoning Network for Textbook Question AnsweringJie Ma 0001, Jun Liu 0002, Yaxian Wang, Junjun Li, Tongliang Liu. tnn, 34(1):15-27, 2023. [doi]

Evolving Semantic Prototype Improves Generative Zero-Shot LearningShiming Chen 0002, Wenjin Hou, Ziming Hong, Xiaohan Ding, Yibing Song, Xinge You, Tongliang Liu, Kun Zhang. icml 2023: 4611-4622 [doi]

A Parametrical Model for Instance-Dependent Label NoiseShuo Yang 0006, Songhua Wu, Erkun Yang, Bo Han 0003, Yang Liu 0018, Min Xu 0001, Gang Niu 0001, Tongliang Liu. pami, 45(12):14055-14068, December 2023. [doi]

Unicom: Universal and Compact Representation Learning for Image RetrievalXiang An, Jiankang deng, Kaicheng Yang, Jaiwei Li, Ziyong Feng, Jia Guo, Jing Yang 0038, Tongliang Liu. iclr 2023: [doi]

Subclass-Dominant Label Noise: A Counterexample for the Success of Early StoppingYingbin Bai, Zhongyi Han, Erkun Yang, Jun Yu, Bo Han, Dadong Wang, Tongliang Liu. nips 2023: [doi]

Towards Label-free Scene Understanding by Vision Foundation ModelsRunnan Chen, Youquan Liu, Lingdong Kong, Nenglun Chen, Xinge Zhu, Yuexin Ma, Tongliang Liu, Wenping Wang. nips 2023: [doi]

HumanMAC: Masked Motion Completion for Human Motion PredictionLing-Hao Chen, Jiawei Zhang, Yewen Li, Yiren Pang, Xiaobo Xia, Tongliang Liu. iccv 2023: 9510-9521 [doi]

Diversity-enhancing Generative Network for Few-shot Hypothesis AdaptationRuijiang Dong, Feng Liu, Haoang Chi, Tongliang Liu, Mingming Gong, Gang Niu 0001, Masashi Sugiyama, Bo Han 0003. icml 2023: 8260-8275 [doi]

FedDAG: Federated DAG Structure LearningErdun Gao, Junjia Chen, Li Shen 0008, Tongliang Liu, Mingming Gong, Howard D. Bondell. tmlr, 2023, 2023. [doi]

Handling Open-Set Noise and Novel Target Recognition in Domain Adaptive Semantic SegmentationXiaoqing Guo, Jie Liu 0044, Tongliang Liu, Yixuan Yuan. pami, 45(8):9846-9861, August 2023. [doi]

Type-I Generative Adversarial AttackShenghong He, Ruxin Wang 0002, Tongliang Liu, Chao Yi, Xin Jin 0005, RenYang Liu, Wei Zhou 0011. tdsc, 20(3):2593-2606, May - June 2023. [doi]

Architecture, Dataset and Model-Scale Agnostic Data-free Meta-LearningZixuan Hu, Li Shen, Zhenyi Wang, Tongliang Liu, Chun Yuan, Dacheng Tao. cvpr 2023: 7736-7745 [doi]

Multiscale Representation for Real-Time Anti-Aliasing Neural RenderingDongting Hu, Zhenkai Zhang, Tingbo Hou, Tongliang Liu, Huan Fu, Mingming Gong. iccv 2023: 17726-17737 [doi]

Harnessing Out-Of-Distribution Examples via Augmenting Content and StyleZhuo Huang, Xiaobo Xia, Li Shen 0008, Bo Han 0003, Mingming Gong, Chen Gong 0002, Tongliang Liu. iclr 2023: [doi]

PADDLES: Phase-Amplitude Spectrum Disentangled Early Stopping for Learning with Noisy LabelsHuaxi Huang, Hui Kang, Sheng Liu, Olivier Salvado, Thierry Rakotoarivelo, Dadong Wang, Tongliang Liu. iccv 2023: 16673-16684 [doi]

Robust Generalization Against Photon-Limited Corruptions via Worst-Case Sharpness MinimizationZhuo Huang, Miaoxi Zhu, Xiaobo Xia, Li Shen 0008, Jun Yu 0001, Chen Gong 0002, Bo Han 0003, Bo Du 0001, Tongliang Liu. cvpr 2023: 16175-16185 [doi]

FlatMatch: Bridging Labeled Data and Unlabeled Data with Cross-Sharpness for Semi-Supervised LearningZhuo Huang, Li Shen 0008, Jun Yu, Bo Han 0003, Tongliang Liu. nips 2023: [doi]

Detecting Out-of-distribution Data through In-distribution Class PriorXue Jiang, Feng Liu, Zhen Fang, Hong Chen 0004, Tongliang Liu, Feng Zheng, Bo Han. icml 2023: 15067-15088 [doi]

Dynamics-aware loss for learning with label noiseXiu-Chuan Li, Xiaobo Xia, Fei Zhu, Tongliang Liu, Xu-Yao Zhang, Cheng-Lin Liu. PR, 144:109835, December 2023. [doi]

Trustable Co-Label Learning From Multiple Noisy AnnotatorsShikun Li, Tongliang Liu, Jiyong Tan, Dan Zeng 0001, Shiming Ge. tmm, 25:1045-1057, 2023. [doi]

InstanT: Semi-supervised Learning with Instance-dependent ThresholdsMuyang Li, Runze Wu, Haoyu Liu, Jun Yu, Xun Yang, Bo Han 0003, Tongliang Liu. nips 2023: [doi]

Contextual Convolutional NetworksShuxian Liang, Xu Shen, Tongliang Liu, Xian-Sheng Hua 0001. iclr 2023: [doi]

Eliminating Catastrophic Overfitting Via Abnormal Adversarial Examples RegularizationRunqi Lin, Chaojian Yu, Tongliang Liu. nips 2023: [doi]

CS-Isolate: Extracting Hard Confident Examples by Content and Style IsolationYexiong Lin, Yu Yao, Xiaolong Shi, Mingming Gong, Xu Shen, Dong Xu 0001, Tongliang Liu. nips 2023: [doi]

A Holistic View of Label Noise Transition Matrix in Deep Learning and BeyondYong Lin, Renjie Pi, Weizhong Zhang, Xiaobo Xia, Jiahui Gao, Xiao Zhou, Tongliang Liu, Bo Han 0003. iclr 2023: [doi]

Graph Pooling for Graph Neural Networks: Progress, Challenges, and OpportunitiesChuang Liu, Yibing Zhan, Jia Wu, Chang Li, Bo Du, Wenbin Hu, Tongliang Liu, Dacheng Tao. IJCAI 2023: 6712-6722 [doi]

On exploring node-feature and graph-structure diversities for node drop graph poolingChuang Liu, Yibing Zhan, Baosheng Yu, Liu Liu 0014, Bo Du 0001, Wenbin Hu, Tongliang Liu. NN, 167:559-571, October 2023. [doi]

Point-Query Quadtree for Crowd Counting, Localization, and MoreChengxin Liu, Hao Lu, Zhiguo Cao 0001, Tongliang Liu. iccv 2023: 1676-1685 [doi]

Recent Advances for Quantum Neural Networks in Generative LearningJinkai Tian, Xiaoyu Sun, Yuxuan Du, Shanshan Zhao 0001, Qing Liu, Kaining Zhang, Wei Yi, Wanrong Huang, Chaoyue Wang, Xingyao Wu, Min-Hsiu Hsieh, Tongliang Liu, Wenjing Yang 0002, Dacheng Tao. pami, 45(10):12321-12340, October 2023. [doi]

Symmetric Pruning in Quantum Neural NetworksXinbiao Wang, Junyu Liu, Tongliang Liu, Yong Luo 0002, Yuxuan Du, Dacheng Tao. iclr 2023: [doi]

Defending against Data-Free Model Extraction by Distributionally Robust Defensive TrainingZhenyi Wang, Li Shen, Tongliang Liu, Tiehang Duan, Yanjun Zhu, Donglin Zhan, David S. Doermann, Mingchen Gao. nips 2023: [doi]

Mosaic Representation Learning for Self-supervised Visual Pre-trainingZhaoqing Wang, Ziyu Chen, Yaqian Li, Yandong Guo, Jun Yu 0002, Mingming Gong, Tongliang Liu. iclr 2023: [doi]

Out-of-distribution Detection with Implicit Outlier TransformationQizhou Wang, Junjie Ye, Feng Liu 0003, Quanyu Dai, Marcus Kalander, Tongliang Liu, Jianye Hao, Bo Han 0003. iclr 2023: [doi]

A Universal Unbiased Method for Classification from Aggregate ObservationsZixi Wei, Lei Feng, Bo Han, Tongliang Liu, Gang Niu 0001, Xiaofeng Zhu 0001, Heng Tao Shen. icml 2023: 36804-36820 [doi]

Holistic Label Correction for Noisy Multi-Label ClassificationXiaobo Xia, Jiankang deng, Wei Bao, Yuxuan Du, Bo Han, Shiguang Shan, Tongliang Liu. iccv 2023: 1483-1493 [doi]

Moderate Coreset: A Universal Method of Data Selection for Real-world Data-efficient Deep LearningXiaobo Xia, Jiale Liu, Jun Yu 0001, Xu Shen, Bo Han 0003, Tongliang Liu. iclr 2023: [doi]

Combating Noisy Labels with Sample Selection by Mining High-Discrepancy ExamplesXiaobo Xia, Bo Han 0003, Yibing Zhan, Jun Yu 0001, Mingming Gong, Chen Gong 0002, Tongliang Liu. iccv 2023: 1833-1843 [doi]

Extended $T$T: Learning With Mixed Closed-Set and Open-Set Noisy LabelsXiaobo Xia, Bo Han 0003, Nannan Wang 0001, Jiankang deng, Jiatong Li, Yinian Mao, Tongliang Liu. pami, 45(3):3047-3058, March 2023. [doi]

PNT-Edge: Towards Robust Edge Detection with Noisy Labels by Learning Pixel-level Noise TransitionsWenjie Xuan, Shanshan Zhao 0001, Yu Yao, Juhua Liu, Tongliang Liu, Yixin Chen, Bo Du 0001, Dacheng Tao. mm 2023: 1924-1932 [doi]

FedFed: Feature Distillation against Data Heterogeneity in Federated LearningZhiqin Yang, Yonggang Zhang, Yu Zheng, Xinmei Tian 0001, Hao Peng, Tongliang Liu, Bo Han 0003. nips 2023: [doi]

ALIP: Adaptive Language-Image Pre-training with Synthetic CaptionKaicheng Yang, Jiankang deng, Xiang An, Jiawei Li, Ziyong Feng, Jia Guo, Jing Yang 0038, Tongliang Liu. iccv 2023: 2910-2919 [doi]

An Efficient Dataset Condensation Plugin and Its Application to Continual LearningEnneng Yang, Li Shen, Zhenyi Wang, Tongliang Liu, Guibing Guo. nips 2023: [doi]

BiCro: Noisy Correspondence Rectification for Multi-modality Data via Bi-directional Cross-modal Similarity ConsistencyShuo Yang, Zhaopan Xu, Kai Wang, Yang You, Hongxun Yao, Tongliang Liu, Min Xu 0001. cvpr 2023: 19883-19892 [doi]

Understanding How Pretraining Regularizes Deep Learning AlgorithmsYu Yao, Baosheng Yu, Chen Gong 0002, Tongliang Liu. tnn, 34(9):5828-5840, September 2023. [doi]

Which is Better for Learning with Noisy Labels: The Semi-supervised Method or Modeling Label Noise?Yu Yao, Mingming Gong, Yuxuan Du, Jun Yu, Bo Han, Kun Zhang, Tongliang Liu. icml 2023: 39660-39673 [doi]

DeepSolo: Let Transformer Decoder with Explicit Points Solo for Text SpottingMaoyuan Ye, Jing Zhang, Shanshan Zhao 0001, Juhua Liu, Tongliang Liu, Bo Du, Dacheng Tao. cvpr 2023: 19348-19357 [doi]

Late Stopping: Avoiding Confidently Learning from Mislabeled ExamplesSuqin Yuan, Lei Feng 0006, Tongliang Liu. iccv 2023: 16033-16042 [doi]

An Optimal Transport Analysis on Generalization in Deep LearningJingwei Zhang, Tongliang Liu, Dacheng Tao. tnn, 34(6):2842-2853, June 2023. [doi]

Out-of-distribution Detection Learning with Unreliable Out-of-distribution SourcesHaotian Zheng, Qizhou Wang, Zhen Fang, Xiaobo Xia, Feng Liu, Tongliang Liu, Bo Han 0003. nips 2023: [doi]

KRADA: Known-region-aware Domain Alignment for Open-set Domain Adaptation in Semantic SegmentationChenhong Zhou, Feng Liu 0003, Chen Gong 0002, Rongfei Zeng, Tongliang Liu, Kwok-Wai Cheung 0001, Bo Han 0003. tmlr, 2023, 2023. [doi]

Eliminating Adversarial Noise via Information Discard and Robust Representation RestorationDawei Zhou, Yukun Chen, Nannan Wang 0001, Decheng Liu, Xinbo Gao 0001, Tongliang Liu. icml 2023: 42517-42530 [doi]

Phase-aware Adversarial Defense for Improving Adversarial RobustnessDawei Zhou, Nannan Wang 0001, Heng Yang, Xinbo Gao 0001, Tongliang Liu. icml 2023: 42724-42741 [doi]

Diversified Outlier Exposure for Out-of-Distribution Detection via Informative ExtrapolationJianing Zhu, Yu Geng, Jiangchao Yao, Tongliang Liu, Gang Niu 0001, Masashi Sugiyama, Bo Han. nips 2023: [doi]

Combating Exacerbated Heterogeneity for Robust Models in Federated LearningJianing Zhu, Jiangchao Yao, Tongliang Liu, Quanming Yao, Jianliang Xu, Bo Han 0003. iclr 2023: [doi]

Unleashing Mask: Explore the Intrinsic Out-of-Distribution Detection CapabilityJianing Zhu, Hengzhuang Li, Jiangchao Yao, Tongliang Liu, Jianliang Xu, Bo Han 0003. icml 2023: 43068-43104 [doi]

Exploring Model Dynamics for Accumulative Poisoning DiscoveryJianing Zhu, Xiawei Guo, Jiangchao Yao, Chao Du, Li He, Shuo Yuan, Tongliang Liu, Liang Wang, Bo Han. icml 2023: 42983-43004 [doi]

2022

Nonlinear Multi-Model ReuseYong Luo 0002, Ling-Yu Duan, Yan Bai, Tongliang Liu, Yihang Lou, Yonggang Wen 0001. mmsp 2022: 1-6 [doi]

Instance-Dependent Positive and Unlabeled Learning With Labeling Bias EstimationChen Gong 0002, Qizhou Wang, Tongliang Liu, Bo Han 0003, Jane You, Jian Yang 0003, Dacheng Tao. pami, 44(8):4163-4177, 2022. [doi]

Understanding and Improving Graph Injection Attack by Promoting UnnoticeabilityYongqiang Chen 0002, Han Yang 0002, Yonggang Zhang, Kaili Ma 0001, Tongliang Liu, Bo Han 0003, James Cheng. iclr 2022: [doi]

Learning Causally Invariant Representations for Out-of-Distribution Generalization on GraphsYongqiang Chen 0002, Yonggang Zhang, Yatao Bian, Han Yang 0002, Kaili Ma 0001, Binghui Xie, Tongliang Liu, Bo Han 0003, James Cheng. nips 2022: [doi]

Unleashing the Potential of Adaptation Models via Go-getting Domain LabelsXin Jin 0014, Tianyu He, Xu Shen, Songhua Wu, Tongliang Liu, Jingwen Ye, Xinchao Wang, Jianqiang Huang, Zhibo Chen 0001, Xian-Sheng Hua 0001. eccv 2023: 308-325 [doi]

Transferable Coupled Network for Zero-Shot Sketch-Based Image RetrievalHao Wang 0062, Cheng Deng, Tongliang Liu, Dacheng Tao. pami, 44(12):9181-9194, 2022. [doi]

Killing Two Birds with One Stone: Efficient and Robust Training of Face Recognition CNNs by Partial FCXiang An, Jiankang deng, Jia Guo, Ziyong Feng, Xuhan Zhu, Jing Yang 0038, Tongliang Liu. cvpr 2022: 4032-4041 [doi]

COVID-MTL: Multitask learning with Shift3D and random-weighted loss for COVID-19 diagnosis and severity assessmentGuoqing Bao, Huai Chen, Tongliang Liu, Guanzhong Gong, Yong Yin, Lisheng Wang, Xiuying Wang. PR, 124:108499, 2022. [doi]

A machine learning approach for predicting human shortest path task performanceShijun Cai, Seok-Hee Hong, Xiaobo Xia, Tongliang Liu, Weidong Huang. vi, 6(2):50-61, 2022. [doi]

A Machine Learning Approach for Predicting Human Preference for Graph LayoutsShijun Cai, Seok-Hee Hong 0001, Jialiang Shen, Tongliang Liu. jgaa, 26(1):447-471, 2022. [doi]

Instance-Dependent Label-Noise Learning with Manifold-Regularized Transition Matrix EstimationDe Cheng, Tongliang Liu, Yixiong Ning, Nannan Wang 0001, Bo Han 0003, Gang Niu 0001, Xinbo Gao 0001, Masashi Sugiyama. cvpr 2022: 16609-16618 [doi]

Class-Dependent Label-Noise Learning with Cycle-Consistency RegularizationDe Cheng, Yixiong Ning, Nannan Wang 0001, Xinbo Gao 0001, Heng Yang, Yuxuan Du, Bo Han 0003, Tongliang Liu. nips 2022: [doi]

Exploring Language Hierarchy for Video GroundingXinpeng Ding, Nannan Wang 0001, Shiwei Zhang, Ziyuan Huang, Xiaomeng Li 0001, Mingqian Tang, Tongliang Liu, Xinbo Gao 0001. TIP, 31:4693-4706, 2022. [doi]

Quantum Differentially Private Sparse Regression LearningYuxuan Du, Min-Hsiu Hsieh, Tongliang Liu, Shan You, Dacheng Tao. TIT, 68(8):5217-5233, 2022. [doi]

Meta Clustering Learning for Large-scale Unsupervised Person Re-identificationXin Jin, Tianyu He, Xu Shen, Tongliang Liu, Xinchao Wang, Jianqiang Huang, Zhibo Chen 0001, Xian-Sheng Hua 0001. mm 2022: 2163-2172 [doi]

Improving Medical Images Classification With Label Noise Using Dual-Uncertainty EstimationLie Ju, Xin Wang 0094, Lin Wang, Dwarikanath Mahapatra, Xin Zhao, Quan Zhou 0004, Tongliang Liu, ZongYuan Ge. tmi, 41(6):1533-1546, 2022. [doi]

Laplacian Welsch Regularization for Robust Semisupervised LearningJingchen Ke, Chen Gong 0002, Tongliang Liu, Lin Zhao, Jian Yang 0003, Dacheng Tao. tcyb, 52(1):164-177, 2022. [doi]

Improving Supervised Learning in Conversational Analysis through Reusing Preprocessing Data as Auxiliary SupervisorsJoshua Y. Kim, Tongliang Liu, Kalina Yacef. icmi 2022: 134-143 [doi]

MAPS: a dataset for semantic profiling and analysis of Android applicationsAmirmohammad Pasdar, Young Choon Lee, Seok-Hee Hong, Tongliang Liu. mobiarch 2022: 13-18 [doi]

Train Me to Fight: Machine-Learning Based On-Device Malware Detection for Mobile DevicesAmirmohammad Pasdar, Young Choon Lee, Tongliang Liu, Seok-Hee Hong. ccgrid 2022: 239-248 [doi]

Learning and Mining with Noisy LabelsMasashi Sugiyama, Tongliang Liu, Bo Han 0003, Yang Liu, Gang Niu 0001. CIKM 2022: 5152-5155 [doi]

Towards Lightweight Black-Box Attack Against Deep Neural NetworksChenghao Sun, Yonggang Zhang, Chaoqun Wan, Qizhou Wang, Ya Li, Tongliang Liu, Bo Han 0003, Xinmei Tian 0001. nips 2022: [doi]

Exploring Set Similarity for Dense Self-supervised Representation LearningZhaoqing Wang, Qiang Li, Guoxin Zhang, Pengfei Wan, Wen Zheng, Nannan Wang 0001, Mingming Gong, Tongliang Liu. cvpr 2022: 16569-16578 [doi]

CRIS: CLIP-Driven Referring Image SegmentationZhaoqing Wang, Yu Lu, Qiang Li, Xunqiang Tao, Yandong Guo, Mingming Gong, Tongliang Liu. cvpr 2022: 11676-11685 [doi]

Learning with Noisy Labels Revisited: A Study Using Real-World Human AnnotationsJiaheng Wei, Zhaowei Zhu, Hao Cheng 0014, Tongliang Liu, Gang Niu 0001, Yang Liu 0018. iclr 2022: [doi]

To Smooth or Not? When Label Smoothing Meets Noisy LabelsJiaheng Wei, Hangyu Liu, Tongliang Liu, Gang Niu 0001, Masashi Sugiyama, Yang Liu. icml 2022: 23589-23614 [doi]

LR-SVM+: Learning Using Privileged Information with Noisy LabelsZhengning Wu, Xiaobo Xia, Ruxin Wang, Jiatong Li, Jun Yu 0001, Yinian Mao, Tongliang Liu. tmm, 24:1080-1092, 2022. [doi]

Learning from Noisy Pairwise Similarity and Unlabeled DataSonghua Wu, Tongliang Liu, Bo Han 0003, Jun Yu 0001, Gang Niu 0001, Masashi Sugiyama. jmlr, 23, 2022. [doi]

Fair Classification with Instance-dependent Label NoiseSonghua Wu, Mingming Gong, Bo Han 0003, Yang Liu 0018, Tongliang Liu. clear2 2022: 927-943 [doi]

Bridging the Gap Between Few-Shot and Many-Shot Learning via Distribution CalibrationShuo Yang, Songhua Wu, Tongliang Liu, Min Xu 0001. pami, 44(12):9830-9843, 2022. [doi]

Rethinking Class-Prior Estimation for Positive-Unlabeled LearningYu Yao, Tongliang Liu, Bo Han 0003, Mingming Gong, Gang Niu 0001, Masashi Sugiyama, Dacheng Tao. iclr 2022: [doi]

On the Rates of Convergence From Surrogate Risk Minimizers to the Bayes Optimal ClassifierJingwei Zhang, Tongliang Liu, Dacheng Tao. tnn, 33(10):5766-5774, 2022. [doi]

Adversarial Robustness Through the Lens of CausalityYonggang Zhang, Mingming Gong, Tongliang Liu, Gang Niu 0001, Xinmei Tian 0001, Bo Han 0003, Bernhard Schölkopf, Kun Zhang 0001. iclr 2022: [doi]

Exploiting Class Activation Value for Partial-Label LearningFei Zhang, Lei Feng, Bo Han 0003, Tongliang Liu, Gang Niu 0001, Tao Qin, Masashi Sugiyama. iclr 2022: [doi]

TWGAN: Twin Discriminator Generative Adversarial NetworksZhaoyu Zhang, Mengyan Li, Haonian Xie, Jun Yu 0001, Tongliang Liu, Chang Wen Chen. tmm, 24:677-688, 2022. [doi]

Modeling Adversarial Noise for Adversarial TrainingDawei Zhou, Nannan Wang, Bo Han, Tongliang Liu. icml 2022: 27353-27366 [doi]

Improving Adversarial Robustness via Mutual Information EstimationDawei Zhou, Nannan Wang 0001, Xinbo Gao 0001, Bo Han 0003, Xiaoyu Wang, Yibing Zhan, Tongliang Liu. icml 2022: 27338-27352 [doi]

Counterfactual Fairness with Partially Known Causal GraphAoqi Zuo, Susan Wei, Tongliang Liu, Bo Han 0003, Kun Zhang 0001, Mingming Gong. nips 2022: [doi]

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