ML Anthology

Wu, Qitian

29 publications

ICLR 2025 DiffPuter: Empowering Diffusion Models for Missing Data Imputation Hengrui Zhang, Liancheng Fang, Qitian Wu, Philip S. Yu
ICML 2025 Generative Modeling Reinvents Supervised Learning: Label Repurposing with Predictive Consistency Learning Yang Li, Jiale Ma, Yebin Yang, Qitian Wu, Hongyuan Zha, Junchi Yan
ICLR 2025 Regularizing Energy Among Training Samples for Out-of-Distribution Generalization Yiting Chen, Qitian Wu, Junchi Yan
ICLR 2025 SLMRec: Distilling Large Language Models into Small for Sequential Recommendation Wujiang Xu, Qitian Wu, Zujie Liang, Jiaojiao Han, Xuying Ning, Yunxiao Shi, Wenfang Lin, Yongfeng Zhang
ICML 2025 Supercharging Graph Transformers with Advective Diffusion Qitian Wu, Chenxiao Yang, Kaipeng Zeng, Michael M. Bronstein
ICML 2025 TabNAT: A Continuous-Discrete Joint Generative Framework for Tabular Data Hengrui Zhang, Liancheng Fang, Qitian Wu, Philip S. Yu
JMLR 2025 Transformers from Diffusion: A Unified Framework for Neural Message Passing Qitian Wu, David Wipf, Junchi Yan
ICML 2024 Graph Out-of-Distribution Detection Goes Neighborhood Shaping Tianyi Bao, Qitian Wu, Zetian Jiang, Yiting Chen, Jiawei Sun, Junchi Yan
ICML 2024 How Graph Neural Networks Learn: Lessons from Training Dynamics Chenxiao Yang, Qitian Wu, David Wipf, Ruoyu Sun, Junchi Yan
ICML 2024 Learning Divergence Fields for Shift-Robust Graph Representations Qitian Wu, Fan Nie, Chenxiao Yang, Junchi Yan
AAAI 2024 TDeLTA: A Light-Weight and Robust Table Detection Method Based on Learning Text Arrangement Yang Fan, Xiangping Wu, Qingcai Chen, Heng Li, Yan Huang, Zhixiang Cai, Qitian Wu
ICLR 2023 DIFFormer: Scalable (Graph) Transformers Induced by Energy Constrained Diffusion Qitian Wu, Chenxiao Yang, Wentao Zhao, Yixuan He, David Wipf, Junchi Yan
ICLR 2023 Energy-Based Out-of-Distribution Detection for Graph Neural Networks Qitian Wu, Yiting Chen, Chenxiao Yang, Junchi Yan
ICLR 2023 Graph Neural Networks Are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs Chenxiao Yang, Qitian Wu, Jiahua Wang, Junchi Yan
NeurIPS 2023 SGFormer: Simplifying and Empowering Transformers for Large-Graph Representations Qitian Wu, Wentao Zhao, Chenxiao Yang, Hengrui Zhang, Fan Nie, Haitian Jiang, Yatao Bian, Junchi Yan
NeurIPS 2023 Unleashing the Power of Graph Data Augmentation on Covariate Distribution Shift Yongduo Sui, Qitian Wu, Jiancan Wu, Qing Cui, Longfei Li, Jun Zhou, Xiang Wang, Xiangnan He
NeurIPS 2022 Geometric Knowledge Distillation: Topology Compression for Graph Neural Networks Chenxiao Yang, Qitian Wu, Junchi Yan
NeurIPS 2022 GraphDE: A Generative Framework for Debiased Learning and Out-of-Distribution Detection on Graphs Zenan Li, Qitian Wu, Fan Nie, Junchi Yan
ICLR 2022 Handling Distribution Shifts on Graphs: An Invariance Perspective Qitian Wu, Hengrui Zhang, Junchi Yan, David Wipf
NeurIPS 2022 Learning Substructure Invariance for Out-of-Distribution Molecular Representations Nianzu Yang, Kaipeng Zeng, Qitian Wu, Xiaosong Jia, Junchi Yan
NeurIPS 2022 NodeFormer: A Scalable Graph Structure Learning Transformer for Node Classification Qitian Wu, Wentao Zhao, Zenan Li, David P Wipf, Junchi Yan
NeurIPS 2022 Towards Out-of-Distribution Sequential Event Prediction: A Causal Treatment Chenxiao Yang, Qitian Wu, Qingsong Wen, Zhiqiang Zhou, Liang Sun, Junchi Yan
IJCAI 2022 Trading Hard Negatives and True Negatives: A Debiased Contrastive Collaborative Filtering Approach Chenxiao Yang, Qitian Wu, Jipeng Jin, Xiaofeng Gao, Junwei Pan, Guihai Chen
NeurIPS 2021 Bridging Explicit and Implicit Deep Generative Models via Neural Stein Estimators Qitian Wu, Rui Gao, Hongyuan Zha
NeurIPS 2021 From Canonical Correlation Analysis to Self-Supervised Graph Neural Networks Hengrui Zhang, Qitian Wu, Junchi Yan, David P. Wipf, Philip S Yu
NeurIPS 2021 Towards Open-World Feature Extrapolation: An Inductive Graph Learning Approach Qitian Wu, Chenxiao Yang, Junchi Yan
ICML 2021 Towards Open-World Recommendation: An Inductive Model-Based Collaborative Filtering Approach Qitian Wu, Hengrui Zhang, Xiaofeng Gao, Junchi Yan, Hongyuan Zha
IJCAI 2019 Feature Evolution Based Multi-Task Learning for Collaborative Filtering with Social Trust Qitian Wu, Lei Jiang, Xiaofeng Gao, Xiaochun Yang, Guihai Chen
NeurIPS 2019 Learning Latent Process from High-Dimensional Event Sequences via Efficient Sampling Qitian Wu, Zixuan Zhang, Xiaofeng Gao, Junchi Yan, Guihai Chen