Gong, Mingming

121 publications

ICLR 2025 A Robust Method to Discover Causal or Anticausal Relation Yu Yao, Yang Zhou, Bo Han, Mingming Gong, Kun Zhang, Tongliang Liu

ICLR 2025 A Skewness-Based Criterion for Addressing Heteroscedastic Noise in Causal Discovery Yingyu Lin, Yuxing Huang, Wenqin Liu, Haoran Deng, Ignavier Ng, Kun Zhang, Mingming Gong, Yian Ma, Biwei Huang

UAI 2025 A Unified Data Representation Learning for Non-Parametric Two-Sample Testing Xunye Tian, Liuhua Peng, Zhijian Zhou, Mingming Gong, Arthur Gretton, Feng Liu

MLJ 2025 Alignclip: Navigating the Misalignments for Robust Vision-Language Generalization Zhongyi Han, Gongxu Luo, Hao Sun, Yaqian Li, Bo Han, Mingming Gong, Kun Zhang, Tongliang Liu

ICLR 2025 Analytic DAG Constraints for Differentiable DAG Learning Zhen Zhang, Ignavier Ng, Dong Gong, Yuhang Liu, Mingming Gong, Biwei Huang, Kun Zhang, Anton van den Hengel, Javen Qinfeng Shi

NeurIPS 2025 Counterfactual Implicit Feedback Modeling Chuan Zhou, Lina Yao, Haoxuan Li, Mingming Gong

AAAI 2025 DIDiffGes: Decoupled Semi-Implicit Diffusion Models for Real-Time Gesture Generation from Speech Yongkang Cheng, Shaoli Huang, Xuelin Chen, Jifeng Ning, Mingming Gong

NeurIPS 2025 Decentralized Dynamic Cooperation of Personalized Models for Federated Continual Learning Danni Yang, Zhikang Chen, Sen Cui, Mengyue Yang, Ding Li, Abudukelimu Wuerkaixi, Haoxuan Li, Jinke Ren, Mingming Gong

NeurIPS 2025 Detecting Generated Images by Fitting Natural Image Distributions Yonggang Zhang, Jun Nie, Xinmei Tian, Mingming Gong, Kun Zhang, Bo Han

ICML 2025 Enhancing Treatment Effect Estimation via Active Learning: A Counterfactual Covering Perspective Hechuan Wen, Tong Chen, Mingming Gong, Li Kheng Chai, Shazia Sadiq, Hongzhi Yin

ICML 2025 Extracting Rare Dependence Patterns via Adaptive Sample Reweighting Yiqing Li, Yewei Xia, Xiaofei Wang, Zhengming Chen, Liuhua Peng, Mingming Gong, Kun Zhang

TMLR 2025 Federated Generalized Novel Category Discovery with Prompts Tuning Lei Shen, Nan Pu, Zhun Zhong, Mingming Gong, Dianhai Yu, Chengqi Zhang, Bo Han

CVPR 2025 LaVin-DiT: Large Vision Diffusion Transformer Zhaoqing Wang, Xiaobo Xia, Runnan Chen, Dongdong Yu, Changhu Wang, Mingming Gong, Tongliang Liu

TMLR 2025 Latent Covariate Shift: Unlocking Partial Identifiability for Multi-Source Domain Adaptation Yuhang Liu, Zhen Zhang, Dong Gong, Mingming Gong, Biwei Huang, Anton van den Hengel, Kun Zhang, Javen Qinfeng Shi

ICML 2025 Learning Imbalanced Data with Beneficial Label Noise Guangzheng Hu, Feng Liu, Mingming Gong, Guanghui Wang, Liuhua Peng

ICLR 2025 LoCA: Location-Aware Cosine Adaptation for Parameter-Efficient Fine-Tuning Zhekai Du, Yinjie Min, Jingjing Li, Ke Lu, Changliang Zou, Liuhua Peng, Tingjin Chu, Mingming Gong

NeurIPS 2025 MLLM-For3D: Adapting Multimodal Large Language Model for 3D Reasoning Segmentation Jiaxin Huang, Runnan Chen, Ziwen Li, Zhengqing Gao, Xiao He, Yandong Guo, Mingming Gong, Tongliang Liu

ICLRW 2025 MMA: Benchmarking Multi-Modal Large Language Model in Ambiguity Contexts Ru Wang, Selena Song, Liang Ding, Mingming Gong, Yusuke Iwasawa, Yutaka Matsuo, Jiaxian Guo

ICML 2025 MissScore: High-Order Score Estimation in the Presence of Missing Data Wenqin Liu, Haoze Hou, Erdun Gao, Biwei Huang, Qiuhong Ke, Howard Bondell, Mingming Gong

ICLR 2025 On the Identification of Temporal Causal Representation with Instantaneous Dependence Zijian Li, Yifan Shen, Kaitao Zheng, Ruichu Cai, Xiangchen Song, Mingming Gong, Guangyi Chen, Kun Zhang

ICLR 2025 Optimal Transport for Time Series Imputation Hao Wang, Zhengnan Li, Haoxuan Li, Xu Chen, Mingming Gong, BinChen, Zhichao Chen

NeurIPS 2025 Practical Kernel Selection for Kernel-Based Conditional Independence Test Wenjie Wang, Mingming Gong, Biwei Huang, James Bailey, Bo Han, Kun Zhang, Feng Liu

ICML 2025 Projection Pursuit Density Ratio Estimation Meilin Wang, Wei Huang, Mingming Gong, Zheng Zhang

ICLRW 2025 RADI: LLMs as World Models for Robotic Action Decomposition and Imagination Dongqi Zuo, Zheng Chen, Chuan Zhou, Yandong Guo, Xiao He, Mingming Gong

CVPR 2025 Semantic-Guided Cross-Modal Prompt Learning for Skeleton-Based Zero-Shot Action Recognition Anqi Zhu, Jingmin Zhu, James Bailey, Mingming Gong, Qiuhong Ke

CVPR 2025 SnapGen: Taming High-Resolution Text-to-Image Models for Mobile Devices with Efficient Architectures and Training Jierun Chen, Dongting Hu, Xijie Huang, Huseyin Coskun, Arpit Sahni, Aarush Gupta, Anujraaj Goyal, Dishani Lahiri, Rajesh Singh, Yerlan Idelbayev, Junli Cao, Yanyu Li, Kwang-Ting Cheng, S.-H. Gary Chan, Mingming Gong, Sergey Tulyakov, Anil Kag, Yanwu Xu, Jian Ren

NeurIPS 2025 Surprise3D: A Dataset for Spatial Understanding and Reasoning in Complex 3D Scenes Jiaxin Huang, Ziwen Li, Hanlue Zhang, Runnan Chen, Zhengqing Gao, Xiao He, Yandong Guo, Wenping Wang, Tongliang Liu, Mingming Gong

NeurIPS 2025 Towards Accurate Time Series Forecasting via Implicit Decoding Xinyu Li, Yuchen Luo, Hao Wang, Haoxuan Li, Liuhua Peng, Feng Liu, Yandong Guo, Kun Zhang, Mingming Gong

CVPR 2025 UNIC-Adapter: Unified Image-Instruction Adapter with Multi-Modal Transformer for Image Generation Lunhao Duan, Shanshan Zhao, Wenjun Yan, Yinglun Li, Qing-Guo Chen, Zhao Xu, Weihua Luo, Kaifu Zhang, Mingming Gong, Gui-Song Xia

ICLR 2024 A Variational Framework for Estimating Continuous Treatment Effects with Measurement Error Erdun Gao, Howard Bondell, Wei Huang, Mingming Gong

CLeaR 2024 Causal Discovery with Mixed Linear and Nonlinear Additive Noise Models: A Scalable Approach Wenqin Liu, Biwei Huang, Erdun Gao, Qiuhong Ke, Howard Bondell, Mingming Gong

MLOSS 2024 Causal-Learn: Causal Discovery in Python Yujia Zheng, Biwei Huang, Wei Chen, Joseph Ramsey, Mingming Gong, Ruichu Cai, Shohei Shimizu, Peter Spirtes, Kun Zhang

NeurIPS 2024 Discovery of the Hidden World with Large Language Models Chenxi Liu, Yongqiang Chen, Tongliang Liu, Mingming Gong, James Cheng, Bo Han, Kun Zhang

CVPR 2024 Enhancing Visual Document Understanding with Contrastive Learning in Large Visual-Language Models Xin Li, Yunfei Wu, Xinghua Jiang, Zhihao Guo, Mingming Gong, Haoyu Cao, Yinsong Liu, Deqiang Jiang, Xing Sun

AAAI 2024 Grab What You Need: Rethinking Complex Table Structure Recognition with Flexible Components Deliberation Hao Liu, Xin Li, Mingming Gong, Bing Liu, Yunfei Wu, Deqiang Jiang, Yinsong Liu, Xing Sun

AAAI 2024 HuTuMotion: Human-Tuned Navigation of Latent Motion Diffusion Models with Minimal Feedback Gaoge Han, Shaoli Huang, Mingming Gong, Jinglei Tang

NeurIPS 2024 Identifiability Analysis of Linear ODE Systems with Hidden Confounders Yuanyuan Wang, Biwei Huang, Wei Huang, Xi Geng, Mingming Gong

JMLR 2024 Identifiability and Asymptotics in Learning Homogeneous Linear ODE Systems from Discrete Observations Yuanyuan Wang, Wei Huang, Mingming Gong, Xi Geng, Tongliang Liu, Kun Zhang, Dacheng Tao

ICLR 2024 Identifiable Latent Polynomial Causal Models Through the Lens of Change Yuhang Liu, Zhen Zhang, Dong Gong, Mingming Gong, Biwei Huang, Anton van den Hengel, Kun Zhang, Javen Qinfeng Shi

ICLR 2024 Improving Non-Transferable Representation Learning by Harnessing Content and Style Ziming Hong, Zhenyi Wang, Li Shen, Yu Yao, Zhuo Huang, Shiming Chen, Chuanwu Yang, Mingming Gong, Tongliang Liu

NeurIPS 2024 In-N-Out: Lifting 2D Diffusion Prior for 3D Object Removal via Tuning-Free Latents Alignment Dongting Hu, Huan Fu, Jiaxian Guo, Liuhua Peng, Tingjin Chu, Feng Liu, Tongliang Liu, Mingming Gong

ICLR 2024 Interventional Fairness on Partially Known Causal Graphs: A Constrained Optimization Approach Aoqi Zuo, Yiqing Li, Susan Wei, Mingming Gong

WACV 2024 Learning Transferable Representations for Image Anomaly Localization Using Dense Pretraining Haitian He, Sarah Erfani, Mingming Gong, Qiuhong Ke

NeurIPS 2024 Neural Collapse Inspired Feature Alignment for Out-of-Distribution Generalization Zhikang Chen, Min Zhang, Sen Cui, Haoxuan Li, Gang Niu, Mingming Gong, Changshui Zhang, Kun Zhang

JMLR 2024 On Causality in Domain Adaptation and Semi-Supervised Learning: An Information-Theoretic Analysis for Parametric Models Xuetong Wu, Mingming Gong, Jonathan H. Manton, Uwe Aickelin, Jingge Zhu

ICML 2024 On the Recoverability of Causal Relations from Temporally Aggregated I.I.D. Data Shunxing Fan, Mingming Gong, Kun Zhang

ICML 2024 Optimal Kernel Choice for Score Function-Based Causal Discovery Wenjie Wang, Biwei Huang, Feng Liu, Xinge You, Tongliang Liu, Kun Zhang, Mingming Gong

CVPR 2024 Part-Aware Unified Representation of Language and Skeleton for Zero-Shot Action Recognition Anqi Zhu, Qiuhong Ke, Mingming Gong, James Bailey

ECCV 2024 Physics-Informed Knowledge Transfer for Underwater Monocular Depth Estimation Jinghe Yang, Mingming Gong, Ye Pu

WACV 2023 Adaptive Local-Component-Aware Graph Convolutional Network for One-Shot Skeleton-Based Action Recognition Anqi Zhu, Qiuhong Ke, Mingming Gong, James Bailey

NeurIPS 2023 CS-Isolate: Extracting Hard Confident Examples by Content and Style Isolation Yexiong Lin, Yu Yao, Xiaolong Shi, Mingming Gong, Xu Shen, Dong Xu, Tongliang Liu

ICCV 2023 Combating Noisy Labels with Sample Selection by Mining High-Discrepancy Examples Xiaobo Xia, Bo Han, Yibing Zhan, Jun Yu, Mingming Gong, Chen Gong, Tongliang Liu

NeurIPS 2023 ConDaFormer: Disassembled Transformer with Local Structure Enhancement for 3D Point Cloud Understanding Lunhao Duan, Shanshan Zhao, Nan Xue, Mingming Gong, Gui-Song Xia, Dacheng Tao

ICML 2023 Diversity-Enhancing Generative Network for Few-Shot Hypothesis Adaptation Ruijiang Dong, Feng Liu, Haoang Chi, Tongliang Liu, Mingming Gong, Gang Niu, Masashi Sugiyama, Bo Han

TMLR 2023 FedDAG: Federated DAG Structure Learning Erdun Gao, Junjia Chen, Li Shen, Tongliang Liu, Mingming Gong, Howard Bondell

ICCV 2023 Generating Dynamic Kernels via Transformers for Lane Detection Ziye Chen, Yu Liu, Mingming Gong, Bo Du, Guoqi Qian, Kate Smith-Miles

NeurIPS 2023 Generator Identification for Linear SDEs with Additive and Multiplicative Noise Yuanyuan Wang, Xi Geng, Wei Huang, Biwei Huang, Mingming Gong

ICLR 2023 Harnessing Out-of-Distribution Examples via Augmenting Content and Style Zhuo Huang, Xiaobo Xia, Li Shen, Bo Han, Mingming Gong, Chen Gong, Tongliang Liu

NeurIPS 2023 Learning World Models with Identifiable Factorization Yuren Liu, Biwei Huang, Zhengmao Zhu, Honglong Tian, Mingming Gong, Yang Yu, Kun Zhang

ICLR 2023 Mosaic Representation Learning for Self-Supervised Visual Pre-Training Zhaoqing Wang, Ziyu Chen, Yaqian Li, Yandong Guo, Jun Yu, Mingming Gong, Tongliang Liu

ICLR 2023 Multi-Domain Image Generation and Translation with Identifiability Guarantees Shaoan Xie, Lingjing Kong, Mingming Gong, Kun Zhang

ICCV 2023 Multiscale Representation for Real-Time Anti-Aliasing Neural Rendering Dongting Hu, Zhenkai Zhang, Tingbo Hou, Tongliang Liu, Huan Fu, Mingming Gong

WACV 2023 Progressive Video Summarization via Multimodal Self-Supervised Learning Haopeng Li, Qiuhong Ke, Mingming Gong, Tom Drummond

NeurIPS 2023 Semi-Implicit Denoising Diffusion Models (SIDDMs) Yanwu Xu, Mingming Gong, Shaoan Xie, Wei Wei, Matthias Grundmann, Kayhan Batmanghelich, Tingbo Hou

CVPR 2023 Unpaired Image-to-Image Translation with Shortest Path Regularization Shaoan Xie, Yanwu Xu, Mingming Gong, Kun Zhang

ICML 2023 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

ICLR 2022 A Relational Intervention Approach for Unsupervised Dynamics Generalization in Model-Based Reinforcement Learning Jiaxian Guo, Mingming Gong, Dacheng Tao

ICLR 2022 Adversarial Robustness Through the Lens of Causality Yonggang Zhang, Mingming Gong, Tongliang Liu, Gang Niu, Xinmei Tian, Bo Han, Bernhard Schölkopf, Kun Zhang

CVPR 2022 Alleviating Semantics Distortion in Unsupervised Low-Level Image-to-Image Translation via Structure Consistency Constraint Jiaxian Guo, Jiachen Li, Huan Fu, Mingming Gong, Kun Zhang, Dacheng Tao

CVPR 2022 CRIS: CLIP-Driven Referring Image Segmentation Zhaoqing Wang, Yu Lu, Qiang Li, Xunqiang Tao, Yandong Guo, Mingming Gong, Tongliang Liu

NeurIPS 2022 Counterfactual Fairness with Partially Known Causal Graph Aoqi Zuo, Susan Wei, Tongliang Liu, Bo Han, Kun Zhang, Mingming Gong

ECCV 2022 Digging into Radiance Grid for Real-Time View Synthesis with Detail Preservation Jian Zhang, Jinchi Huang, Bowen Cai, Huan Fu, Mingming Gong, Chaohui Wang, Jiaming Wang, Hongchen Luo, Rongfei Jia, Binqiang Zhao, Xing Tang

CVPR 2022 Exploring Set Similarity for Dense Self-Supervised Representation Learning Zhaoqing Wang, Qiang Li, Guoxin Zhang, Pengfei Wan, Wen Zheng, Nannan Wang, Mingming Gong, Tongliang Liu

CLeaR 2022 Fair Classification with Instance-Dependent Label Noise Songhua Wu, Mingming Gong, Bo Han, Yang Liu, Tongliang Liu

CVPR 2022 Few-Shot Font Generation by Learning Fine-Grained Local Styles Licheng Tang, Yiyang Cai, Jiaming Liu, Zhibin Hong, Mingming Gong, Minhu Fan, Junyu Han, Jingtuo Liu, Errui Ding, Jingdong Wang

CVPR 2022 Maximum Spatial Perturbation Consistency for Unpaired Image-to-Image Translation Yanwu Xu, Shaoan Xie, Wenhao Wu, Kun Zhang, Mingming Gong, Kayhan Batmanghelich

NeurIPS 2022 MissDAG: Causal Discovery in the Presence of Missing Data with Continuous Additive Noise Models Erdun Gao, Ignavier Ng, Mingming Gong, Li Shen, Wei Huang, Tongliang Liu, Kun Zhang, Howard Bondell

ICLR 2022 Rethinking Class-Prior Estimation for Positive-Unlabeled Learning Yu Yao, Tongliang Liu, Bo Han, Mingming Gong, Gang Niu, Masashi Sugiyama, Dacheng Tao

IJCAI 2022 Robust Weight Perturbation for Adversarial Training Chaojian Yu, Bo Han, Mingming Gong, Li Shen, Shiming Ge, Du Bo, Tongliang Liu

ICLR 2022 Sample Selection with Uncertainty of Losses for Learning with Noisy Labels Xiaobo Xia, Tongliang Liu, Bo Han, Mingming Gong, Jun Yu, Gang Niu, Masashi Sugiyama

NeurIPS 2022 Truncated Matrix Power Iteration for Differentiable DAG Learning Zhen Zhang, Ignavier Ng, Dong Gong, Yuhang Liu, Ehsan Abbasnejad, Mingming Gong, Kun Zhang, Javen Qinfeng Shi

ECCV 2022 Uncertainty Quantification in Depth Estimation via Constrained Ordinal Regression Dongting Hu, Liuhua Peng, Tingjin Chu, Xiaoxing Zhang, Yinian Mao, Howard Bondell, Mingming Gong

ICML 2022 Understanding Robust Overfitting of Adversarial Training and Beyond Chaojian Yu, Bo Han, Li Shen, Jun Yu, Chen Gong, Mingming Gong, Tongliang Liu

ICML 2021 Class2Simi: A Noise Reduction Perspective on Learning with Noisy Labels Songhua Wu, Xiaobo Xia, Tongliang Liu, Bo Han, Mingming Gong, Nannan Wang, Haifeng Liu, Gang Niu

NeurIPS 2021 Domain Adaptation with Invariant Representation Learning: What Transformations to Learn? Petar Stojanov, Zijian Li, Mingming Gong, Ruichu Cai, Jaime G. Carbonell, Kun Zhang

NeurIPS 2021 Instance-Dependent Label-Noise Learning Under a Structural Causal Model Yu Yao, Tongliang Liu, Mingming Gong, Bo Han, Gang Niu, Kun Zhang

AAAI 2021 Learning with Group Noise Qizhou Wang, Jiangchao Yao, Chen Gong, Tongliang Liu, Mingming Gong, Hongxia Yang, Bo Han

ICCV 2021 Not All Operations Contribute Equally: Hierarchical Operation-Adaptive Predictor for Neural Architecture Search Ziye Chen, Yibing Zhan, Baosheng Yu, Mingming Gong, Bo Du

ICCV 2021 Unaligned Image-to-Image Translation by Learning to Reweight Shaoan Xie, Mingming Gong, Yanwu Xu, Kun Zhang

IJCAI 2020 Bridging Causality and Learning: How Do They Benefit from Each Other? Mingming Gong

AAAI 2020 Causal Discovery from Multiple Data Sets with Non-Identical Variable Sets Biwei Huang, Kun Zhang, Mingming Gong, Clark Glymour

AAAI 2020 Compressed Self-Attention for Deep Metric Learning Ziye Chen, Mingming Gong, Yanwu Xu, Chaohui Wang, Kun Zhang, Bo Du

IJCAI 2020 Compressed Self-Attention for Deep Metric Learning with Low-Rank Approximation Ziye Chen, Mingming Gong, Lingjuan Ge, Bo Du

NeurIPS 2020 Domain Adaptation as a Problem of Inference on Graphical Models Kun Zhang, Mingming Gong, Petar Stojanov, Biwei Huang, Qingsong Liu, Clark Glymour

NeurIPS 2020 Domain Generalization via Entropy Regularization Shanshan Zhao, Mingming Gong, Tongliang Liu, Huan Fu, Dacheng Tao

NeurIPS 2020 Dual T: Reducing Estimation Error for Transition Matrix in Label-Noise Learning Yu Yao, Tongliang Liu, Bo Han, Mingming Gong, Jiankang Deng, Gang Niu, Masashi Sugiyama

AAAI 2020 Generative-Discriminative Complementary Learning Yanwu Xu, Mingming Gong, Junxiang Chen, Tongliang Liu, Kun Zhang, Kayhan Batmanghelich

NeurIPS 2020 Hard Example Generation by Texture Synthesis for Cross-Domain Shape Similarity Learning Huan Fu, Shunming Li, Rongfei Jia, Mingming Gong, Binqiang Zhao, Dacheng Tao

ICML 2020 LTF: A Label Transformation Framework for Correcting Label Shift Jiaxian Guo, Mingming Gong, Tongliang Liu, Kun Zhang, Dacheng Tao

ICML 2020 Label-Noise Robust Domain Adaptation Xiyu Yu, Tongliang Liu, Mingming Gong, Kun Zhang, Kayhan Batmanghelich, Dacheng Tao

NeurIPS 2020 Part-Dependent Label Noise: Towards Instance-Dependent Label Noise Xiaobo Xia, Tongliang Liu, Bo Han, Nannan Wang, Mingming Gong, Haifeng Liu, Gang Niu, Dacheng Tao, Masashi Sugiyama

ECCV 2020 Short-Term and Long-Term Context Aggregation Network for Video Inpainting Ang Li, Shanshan Zhao, Xingjun Ma, Mingming Gong, Jianzhong Qi, Rui Zhang, Dacheng Tao, Ramamohanarao Kotagiri

ECCV 2020 Sub-Center ArcFace: Boosting Face Recognition by Large-Scale Noisy Web Faces Jiankang Deng, Jia Guo, Tongliang Liu, Mingming Gong, Stefanos Zafeiriou

ICML 2019 Causal Discovery and Forecasting in Nonstationary Environments with State-Space Models Biwei Huang, Kun Zhang, Mingming Gong, Clark Glymour

AISTATS 2019 Data-Driven Approach to Multiple-Source Domain Adaptation Petar Stojanov, Mingming Gong, Jaime Carbonell, Kun Zhang

NeurIPS 2019 Likelihood-Free Overcomplete ICA and Applications in Causal Discovery Chenwei Ding, Mingming Gong, Kun Zhang, Dacheng Tao

AISTATS 2019 Low-Dimensional Density Ratio Estimation for Covariate Shift Correction Petar Stojanov, Mingming Gong, Jaime Carbonell, Kun Zhang

NeurIPS 2019 Specific and Shared Causal Relation Modeling and Mechanism-Based Clustering Biwei Huang, Kun Zhang, Pengtao Xie, Mingming Gong, Eric P Xing, Clark Glymour

NeurIPS 2019 Twin Auxilary Classifiers GAN Mingming Gong, Yanwu Xu, Chunyuan Li, Kun Zhang, Kayhan Batmanghelich

UAI 2018 Causal Discovery with Linear Non-Gaussian Models Under Measurement Error: Structural Identifiability Results Kun Zhang, Mingming Gong, Joseph D. Ramsey, Kayhan Batmanghelich, Peter Spirtes, Clark Glymour

ECCV 2018 Correcting the Triplet Selection Bias for Triplet Loss Baosheng Yu, Tongliang Liu, Mingming Gong, Changxing Ding, Dacheng Tao

ECCV 2018 Deep Domain Generalization via Conditional Invariant Adversarial Networks Ya Li, Xinmei Tian, Mingming Gong, Yajing Liu, Tongliang Liu, Kun Zhang, Dacheng Tao

AAAI 2018 Domain Generalization via Conditional Invariant Representations Ya Li, Mingming Gong, Xinmei Tian, Tongliang Liu, Dacheng Tao

ECCV 2018 Learning with Biased Complementary Labels Xiyu Yu, Tongliang Liu, Mingming Gong, Dacheng Tao

NeurIPS 2018 Modeling Dynamic Missingness of Implicit Feedback for Recommendation Menghan Wang, Mingming Gong, Xiaolin Zheng, Kun Zhang

ICCV 2017 A Coarse-Fine Network for Keypoint Localization Shaoli Huang, Mingming Gong, Dacheng Tao

UAI 2017 Causal Discovery from Temporally Aggregated Time Series Mingming Gong, Kun Zhang, Bernhard Schölkopf, Clark Glymour, Dacheng Tao

ICML 2016 Domain Adaptation with Conditional Transferable Components Mingming Gong, Kun Zhang, Tongliang Liu, Dacheng Tao, Clark Glymour, Bernhard Schölkopf

ICML 2015 Causal Inference by Identification of Vector Autoregressive Processes with Hidden Components Philipp Geiger, Kun Zhang, Bernhard Schoelkopf, Mingming Gong, Dominik Janzing

ICML 2015 Discovering Temporal Causal Relations from Subsampled Data Mingming Gong, Kun Zhang, Bernhard Schoelkopf, Dacheng Tao, Philipp Geiger

AAAI 2015 Multi-Source Domain Adaptation: A Causal View Kun Zhang, Mingming Gong, Bernhard Schölkopf