Su, Qinliang

16 publications

AAAI 2025 Boosting Fine-Grained Visual Anomaly Detection with Coarse-Knowledge-Aware Adversarial Learning Qingqing Fang, Qinliang Su, Wenxi Lv, Wenchao Xu, Jianxing Yu

NeurIPS 2025 HoT-VI: Reparameterizable Variational Inference for Capturing Instance-Level High-Order Correlations Junxi Xiao, Qinliang Su, Zexin Yuan

ICLR 2025 One-for-All Few-Shot Anomaly Detection via Instance-Induced Prompt Learning Wenxi Lv, Qinliang Su, Wenchao Xu

ICML 2024 Contamination-Resilient Anomaly Detection via Adversarial Learning on Partially-Observed Normal and Anomalous Data Wenxi Lv, Qinliang Su, Hai Wan, Hongteng Xu, Wenchao Xu

NeurIPS 2024 TreeVI: Reparameterizable Tree-Structured Variational Inference for Instance-Level Correlation Capturing Junxi Xiao, Qinliang Su

AAAI 2023 A Graph Fusion Approach for Cross-Lingual Machine Reading Comprehension Zenan Xu, Linjun Shou, Jian Pei, Ming Gong, Qinliang Su, Xiaojun Quan, Daxin Jiang

IJCAI 2023 Learning Summary-Worthy Visual Representation for Abstractive Summarization in Video Zenan Xu, Xiaojun Meng, Yasheng Wang, Qinliang Su, Zexuan Qiu, Xin Jiang, Qun Liu

AAAI 2023 Leveraging Contaminated Datasets to Learn Clean-Data Distribution with Purified Generative Adversarial Networks Bowen Tian, Qinliang Su, Jianxing Yu

IJCAI 2022 Anomaly Detection by Leveraging Incomplete Anomalous Knowledge with Anomaly-Aware Bidirectional GANs Bowen Tian, Qinliang Su, Jian Yin

NeurIPS 2022 Learning Neural Set Functions Under the Optimal Subset Oracle Zijing Ou, Tingyang Xu, Qinliang Su, Yingzhen Li, Peilin Zhao, Yatao Bian

IJCAI 2021 Unsupervised Hashing with Contrastive Information Bottleneck Zexuan Qiu, Qinliang Su, Zijing Ou, Jianxing Yu, Changyou Chen

AAAI 2018 Deconvolutional Latent-Variable Model for Text Sequence Matching Dinghan Shen, Yizhe Zhang, Ricardo Henao, Qinliang Su, Lawrence Carin

AISTATS 2018 Symmetric Variational Autoencoder and Connections to Adversarial Learning Liqun Chen, Shuyang Dai, Yunchen Pu, Erjin Zhou, Chunyuan Li, Qinliang Su, Changyou Chen, Lawrence Carin

NeurIPS 2017 A Probabilistic Framework for Nonlinearities in Stochastic Neural Networks Qinliang Su, Xuejun Liao, Lawrence Carin

AAAI 2017 Unsupervised Learning with Truncated Gaussian Graphical Models Qinliang Su, Xuejun Liao, Chunyuan Li, Zhe Gan, Lawrence Carin

ICML 2016 Nonlinear Statistical Learning with Truncated Gaussian Graphical Models Qinliang Su, Xuejun Liao, Changyou Chen, Lawrence Carin