Qitian Wu - RankMe

75 papers A* 38A 3Journal 32Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Can Molecular Foundation Models Know What They Don't Know? A Simple Remedy with Preference Optimization. CoRR Langzhou He, Junyou Zhu, Fangxin Wang, Junhua Liu, Haoyan Xu, Yue Zhao, Philip S. Yu, Qitian Wu
2025	A*	`conf`	DiffPuter: Empowering Diffusion Models for Missing Data Imputation. ICLR Hengrui Zhang, Liancheng Fang, Qitian Wu, Philip S. Yu
2025	A*	`conf`	Generative Modeling Reinvents Supervised Learning: Label Repurposing with Predictive Consistency Learning. ICML Yang Li, Jiale Ma, Yebin Yang, Qitian Wu, Hongyuan Zha, Junchi Yan
2025	J	`jnl`	Physics-Inspired All-Pair Interaction Learning for 3D Dynamics Modeling. CoRR Kai Yang, Yuqi Huang, Junheng Tao, Wanyu Wang, Qitian Wu
2025	A*	`conf`	Regularizing Energy among Training Samples for Out-of-Distribution Generalization. ICLR Yiting Chen, Qitian Wu, Junchi Yan
2025	A*	`conf`	SLMRec: Distilling Large Language Models into Small for Sequential Recommendation. ICLR Wujiang Xu, Qitian Wu, Zujie Liang, Jiaojiao Han, Xuying Ning, Yunxiao Shi, Wenfang Lin, Yongfeng Zhang
2025	A*	`conf`	Supercharging Graph Transformers with Advective Diffusion. ICML Qitian Wu, Chenxiao Yang, Kaipeng Zeng, Michael M. Bronstein
2025	A*	`conf`	TabNAT: A Continuous-Discrete Joint Generative Framework for Tabular Data. ICML Hengrui Zhang, Liancheng Fang, Qitian Wu, Philip S. Yu
2025	J	`jnl`	Transformers from Diffusion: A Unified Framework for Neural Message Passing. J. Mach. Learn. Res. Qitian Wu, David Wipf, Junchi Yan
2024	J	`jnl`	Diffusion-nested Auto-Regressive Synthesis of Heterogeneous Tabular Data. CoRR Hengrui Zhang, Liancheng Fang, Qitian Wu, Philip S. Yu
2024	A*	`conf`	GeoMix: Towards Geometry-Aware Data Augmentation. KDD Wentao Zhao, Qitian Wu, Chenxiao Yang, Junchi Yan
2024	J	`jnl`	GeoMix: Towards Geometry-Aware Data Augmentation. CoRR Wentao Zhao, Qitian Wu, Chenxiao Yang, Junchi Yan
2024	A*	`conf`	Graph Out-of-Distribution Detection Goes Neighborhood Shaping. ICML Tianyi Bao, Qitian Wu, Zetian Jiang, Yiting Chen, Jiawei Sun, Junchi Yan
2024	A*	`conf`	Graph Out-of-Distribution Generalization via Causal Intervention. WWW Qitian Wu, Fan Nie, Chenxiao Yang, Tianyi Bao, Junchi Yan
2024	J	`jnl`	Graph Out-of-Distribution Generalization via Causal Intervention. CoRR Qitian Wu, Fan Nie, Chenxiao Yang, Tianyi Bao, Junchi Yan
2024	A*	`conf`	How Graph Neural Networks Learn: Lessons from Training Dynamics. ICML Chenxiao Yang, Qitian Wu, David Wipf, Ruoyu Sun, Junchi Yan
2024	A	`conf`	InfoMLP: Unlocking the Potential of MLPs for Semi-Supervised Learning with Structured Data. CIKM Hengrui Zhang, Qitian Wu, Chenxiao Yang, Philip S. Yu
2024	A*	`conf`	Learning Divergence Fields for Shift-Robust Graph Representations. ICML Qitian Wu, Fan Nie, Chenxiao Yang, Junchi Yan
2024	J	`jnl`	Learning Divergence Fields for Shift-Robust Graph Representations. CoRR Qitian Wu, Fan Nie, Chenxiao Yang, Junchi Yan
2024	J	`jnl`	Neural Message Passing Induced by Energy-Constrained Diffusion. CoRR Qitian Wu, David Wipf, Junchi Yan
2024	A*	`conf`	Rethinking Cross-Domain Sequential Recommendation under Open-World Assumptions. WWW Wujiang Xu, Qitian Wu, Runzhong Wang, Mingming Ha, Qiongxu Ma, Linxun Chen, Bing Han, Junchi Yan
2024	J	`jnl`	SGFormer: Single-Layer Graph Transformers with Approximation-Free Linear Complexity. CoRR Qitian Wu, Kai Yang, Hengrui Zhang, David Wipf, Junchi Yan
2024	J	`jnl`	ScaleGCN: Efficient and Effective Graph Convolution via Channel-Wise Scale Transformation. IEEE Trans. Neural Networks Learn. Syst. Tianqi Zhang, Qitian Wu, Junchi Yan, Yunan Zhao, Bing Han
2024	A*	`conf`	TDeLTA: A Light-Weight and Robust Table Detection Method Based on Learning Text Arrangement. AAAI Yang Fan, Xiangping Wu, Qingcai Chen, Heng Li, Yan Huang, Zhixiang Cai, Qitian Wu
2023	J	`jnl`	Advective Diffusion Transformers for Topological Generalization in Graph Learning. CoRR Qitian Wu, Chenxiao Yang, Kaipeng Zeng, Fan Nie, Michael M. Bronstein, Junchi Yan
2023	A*	`conf`	DIFFormer: Scalable (Graph) Transformers Induced by Energy Constrained Diffusion. ICLR Qitian Wu, Chenxiao Yang, Wentao Zhao, Yixuan He, David Wipf, Junchi Yan
2023	J	`jnl`	DIFFormer: Scalable (Graph) Transformers Induced by Energy Constrained Diffusion. CoRR Qitian Wu, Chenxiao Yang, Wentao Zhao, Yixuan He, David Wipf, Junchi Yan
2023	A*	`conf`	Energy-based Out-of-Distribution Detection for Graph Neural Networks. ICLR Qitian Wu, Yiting Chen, Chenxiao Yang, Junchi Yan
2023	J	`jnl`	Energy-based Out-of-Distribution Detection for Graph Neural Networks. CoRR Qitian Wu, Yiting Chen, Chenxiao Yang, Junchi Yan
2023	A*	`conf`	Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs. ICLR Chenxiao Yang, Qitian Wu, Jiahua Wang, Junchi Yan
2023	A*	`conf`	GraphGLOW: Universal and Generalizable Structure Learning for Graph Neural Networks. KDD Wentao Zhao, Qitian Wu, Chenxiao Yang, Junchi Yan
2023	J	`jnl`	GraphGLOW: Universal and Generalizable Structure Learning for Graph Neural Networks. CoRR Wentao Zhao, Qitian Wu, Chenxiao Yang, Junchi Yan
2023	J	`jnl`	How Graph Neural Networks Learn: Lessons from Training Dynamics in Function Space. CoRR Chenxiao Yang, Qitian Wu, David Wipf, Ruoyu Sun, Junchi Yan
2023	J	`jnl`	Learning High-Order Graph Convolutional Networks via Adaptive Layerwise Aggregation Combination. IEEE Trans. Neural Networks Learn. Syst. Tianqi Zhang, Qitian Wu, Junchi Yan
2023	A*	`conf`	MoleRec: Combinatorial Drug Recommendation with Substructure-Aware Molecular Representation Learning. WWW Nianzu Yang, Kaipeng Zeng, Qitian Wu, Junchi Yan
2023	J	`jnl`	NodeFormer: A Scalable Graph Structure Learning Transformer for Node Classification. CoRR Qitian Wu, Wentao Zhao, Zenan Li, David Wipf, Junchi Yan
2023	J	`jnl`	Rethinking Cross-Domain Sequential Recommendation under Open-World Assumptions. CoRR Wujiang Xu, Qitian Wu, Runzhong Wang, Mingming Ha, Qiongxu Ma, Linxun Chen, Bing Han, Junchi Yan
2023	A*	`conf`	Simplifying and Empowering Transformers for Large-Graph Representations. NeurIPS Qitian Wu, Wentao Zhao, Chenxiao Yang, Hengrui Zhang, Fan Nie, Haitian Jiang, Yatao Bian, Junchi Yan
2023	J	`jnl`	Simplifying and Empowering Transformers for Large-Graph Representations. CoRR Qitian Wu, Wentao Zhao, Chenxiao Yang, Hengrui Zhang, Fan Nie, Haitian Jiang, Yatao Bian, Junchi Yan
2023	J	`jnl`	TDeLTA: A Light-weight and Robust Table Detection Method based on Learning Text Arrangement. CoRR Yang Fan, Xiangping Wu, Qingcai Chen, Heng Li, Yan Huang, Zhixiang Cai, Qitian Wu
2023	A*	`conf`	Unleashing the Power of Graph Data Augmentation on Covariate Distribution Shift. NeurIPS Yongduo Sui, Qitian Wu, Jiancan Wu, Qing Cui, Longfei Li, Jun Zhou, Xiang Wang, Xiangnan He
2022	A*	`conf`	DICE: Domain-attack Invariant Causal Learning for Improved Data Privacy Protection and Adversarial Robustness. KDD Qibing Ren, Yiting Chen, Yichuan Mo, Qitian Wu, Junchi Yan
2022	A*	`conf`	Geometric Knowledge Distillation: Topology Compression for Graph Neural Networks. NeurIPS Chenxiao Yang, Qitian Wu, Junchi Yan
2022	J	`jnl`	Geometric Knowledge Distillation: Topology Compression for Graph Neural Networks. CoRR Chenxiao Yang, Qitian Wu, Junchi Yan
2022	J	`jnl`	Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs. CoRR Chenxiao Yang, Qitian Wu, Jiahua Wang, Junchi Yan
2022	A*	`conf`	GraphDE: A Generative Framework for Debiased Learning and Out-of-Distribution Detection on Graphs. NeurIPS Zenan Li, Qitian Wu, Fan Nie, Junchi Yan
2022	A*	`conf`	Handling Distribution Shifts on Graphs: An Invariance Perspective. ICLR Qitian Wu, Hengrui Zhang, Junchi Yan, David Wipf
2022	A*	`conf`	Learning Substructure Invariance for Out-of-Distribution Molecular Representations. NeurIPS Nianzu Yang, Kaipeng Zeng, Qitian Wu, Xiaosong Jia, Junchi Yan
2022	J	`jnl`	Localized Contrastive Learning on Graphs. CoRR Hengrui Zhang, Qitian Wu, Yu Wang, Shaofeng Zhang, Junchi Yan, Philip S. Yu
2022	A*	`conf`	NodeFormer: A Scalable Graph Structure Learning Transformer for Node Classification. NeurIPS Qitian Wu, Wentao Zhao, Zenan Li, David P. Wipf, Junchi Yan
2022	J	`jnl`	Towards Distribution Shift of Node-Level Prediction on Graphs: An Invariance Perspective. CoRR Qitian Wu, Hengrui Zhang, Junchi Yan, David Wipf
2022	A*	`conf`	Towards Out-of-Distribution Sequential Event Prediction: A Causal Treatment. NeurIPS Chenxiao Yang, Qitian Wu, Qingsong Wen, Zhiqiang Zhou, Liang Sun, Junchi Yan
2022	J	`jnl`	Towards Out-of-Distribution Sequential Event Prediction: A Causal Treatment. CoRR Chenxiao Yang, Qitian Wu, Qingsong Wen, Zhiqiang Zhou, Liang Sun, Junchi Yan
2022	A*	`conf`	Trading Hard Negatives and True Negatives: A Debiased Contrastive Collaborative Filtering Approach. IJCAI Chenxiao Yang, Qitian Wu, Jipeng Jin, Xiaofeng Gao, Junwei Pan, Guihai Chen
2022	J	`jnl`	Trading Hard Negatives and True Negatives: A Debiased Contrastive Collaborative Filtering Approach. CoRR Chenxiao Yang, Qitian Wu, Jipeng Jin, Xiaofeng Gao, Junwei Pan, Guihai Chen
2022	A*	`conf`	Variational Inference for Training Graph Neural Networks in Low-Data Regime through Joint Structure-Label Estimation. KDD Danning Lao, Xinyu Yang, Qitian Wu, Junchi Yan
2021	A*	`conf`	Bridging Explicit and Implicit Deep Generative Models via Neural Stein Estimators. NeurIPS Qitian Wu, Rui Gao, Hongyuan Zha
2021	A*	`conf`	From Canonical Correlation Analysis to Self-supervised Graph Neural Networks. NeurIPS Hengrui Zhang, Qitian Wu, Junchi Yan, David Wipf, Philip S. Yu
2021	J	`jnl`	From Canonical Correlation Analysis to Self-supervised Graph Neural Networks. CoRR Hengrui Zhang, Qitian Wu, Junchi Yan, David Wipf, Philip S. Yu
2021	A	`conf`	Seq2Bubbles: Region-Based Embedding Learning for User Behaviors in Sequential Recommenders. CIKM Qitian Wu, Chenxiao Yang, Shuodian Yu, Xiaofeng Gao, Guihai Chen
2021	A*	`conf`	Towards Open-World Feature Extrapolation: An Inductive Graph Learning Approach. NeurIPS Qitian Wu, Chenxiao Yang, Junchi Yan
2021	J	`jnl`	Towards Open-World Feature Extrapolation: An Inductive Graph Learning Approach. CoRR Qitian Wu, Chenxiao Yang, Junchi Yan
2021	A*	`conf`	Towards Open-World Recommendation: An Inductive Model-based Collaborative Filtering Approach. ICML Qitian Wu, Hengrui Zhang, Xiaofeng Gao, Junchi Yan, Hongyuan Zha
2020	J	`jnl`	Inductive Relational Matrix Completion. CoRR Qitian Wu, Hengrui Zhang, Hongyuan Zha
2020	—	`conf`	SentiMem: Attentive Memory Networks for Sentiment Classification in User Review. DASFAA (1) Xiaosong Jia, Qitian Wu, Xiaofeng Gao, Guihai Chen
2019	A*	`conf`	Dual Graph Attention Networks for Deep Latent Representation of Multifaceted Social Effects in Recommender Systems. WWW Qitian Wu, Hengrui Zhang, Xiaofeng Gao, Peng He, Paul Weng, Han Gao, Guihai Chen
2019	J	`jnl`	Dual Graph Attention Networks for Deep Latent Representation of Multifaceted Social Effects in Recommender Systems. CoRR Qitian Wu, Hengrui Zhang, Xiaofeng Gao, Peng He, Paul Weng, Han Gao, Guihai Chen
2019	A*	`conf`	Dual Sequential Prediction Models Linking Sequential Recommendation and Information Dissemination. KDD Qitian Wu, Yirui Gao, Xiaofeng Gao, Paul Weng, Guihai Chen
2019	A*	`conf`	Feature Evolution Based Multi-Task Learning for Collaborative Filtering with Social Trust. IJCAI Qitian Wu, Lei Jiang, Xiaofeng Gao, Xiaochun Yang, Guihai Chen
2019	A*	`conf`	Learning Latent Process from High-Dimensional Event Sequences via Efficient Sampling. NeurIPS Qitian Wu, Zixuan Zhang, Xiaofeng Gao, Junchi Yan, Guihai Chen
2019	J	`jnl`	Learning Latent Process from High-Dimensional Event Sequences via Efficient Sampling. CoRR Qitian Wu, Zixuan Zhang, Xiaofeng Gao, Junchi Yan, Guihai Chen
2019	J	`jnl`	Stein Bridging: Enabling Mutual Reinforcement between Explicit and Implicit Generative Models. CoRR Qitian Wu, Rui Gao, Hongyuan Zha
2018	A	`conf`	Adversarial Training Model Unifying Feature Driven and Point Process Perspectives for Event Popularity Prediction. CIKM Qitian Wu, Chaoqi Yang, Hengrui Zhang, Xiaofeng Gao, Paul Weng, Guihai Chen
2018	A*	`conf`	EPAB: Early Pattern Aware Bayesian Model for Social Content Popularity Prediction. ICDM Qitian Wu, Chaoqi Yang, Xiaofeng Gao, Peng He, Guihai Chen
2018	—	`conf`	EPOC: A Survival Perspective Early Pattern Detection Model for Outbreak Cascades. DEXA (1) Chaoqi Yang, Qitian Wu, Xiaofeng Gao, Guihai Chen