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Qitian Wu

29 papers · 2019–2025 · 6 venues · across top CS/AI venues

Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.

Achievements

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+9 more ↓ πŸ—ΊοΈ Taxonomy Completionist (43) 🌍 Conference Polyglot Β· Silver πŸƒ Academic Marathon Β· Sprint πŸŒ‰ Interdisciplinary Bridge Β· Bronze 🐣 Hot Topic Early Bird
🧬 Topic Evolution 🀝 Dynamic Duo (20) πŸ† Grand Slam πŸ”¬ Deep Specialist (13) 🌈 Renaissance Researcher (5) πŸ”₯ Unstoppable Β· Bronze ⚑ Prolific Year Β· Productive πŸ’Ž Century Club Β· Bronze πŸ—ƒοΈ Keyword Collector (132)

Venues

NeurIPS (11) ICLR (7) ICML (7) IJCAI (2) AAAI (1) JMLR (1)

Top co-authors

Junchi Yan (20) Chenxiao Yang (11) Hengrui Zhang (6) Xiaofeng Gao (4) David Wipf (4) Fan Nie (3) Yiting Chen (3) Hongyuan Zha (3) Guihai Chen (3) Wentao Zhao (3)

Research topics

Machine Learning (22) Deep Learning (21) Architectures (14) Core Methods (11) Application Areas (10) Artificial Intelligence (8) Learning Types Β· Machine Learning (8) Learning Types Β· Deep Learning (7) Models (7) Core AI (4) Learning Paradigms (4) Optimization & Theory (4) Data Science & Analytics (3) Applications (3) Computer Science (1)

Keywords

graph neural network (12) out-of-distribution generalization (4) diffusion model (4) distribution shift (4) message passing (4) causal inference (3) representation learning (3) node classification (3) collaborative filtering (3) domain generalization (3) ood detection (2) variational inference (2) sequential recommendation (2) invariant learning (2) out-of-distribution detection (2) inductive learning (2) generative model (2) self-supervised learning (2) generalization error (2) knowledge distillation (2)

Papers

DiffPuter: Empowering Diffusion Models for Missing Data Imputation ICLR 2025 Generative Modeling Reinvents Supervised Learning: Label Repurposing with Predictive Consistency Learning ICML 2025 Regularizing Energy among Training Samples for Out-of-Distribution Generalization ICLR 2025 SLMRec: Distilling Large Language Models into Small for Sequential Recommendation ICLR 2025 Supercharging Graph Transformers with Advective Diffusion ICML 2025 TabNAT: A Continuous-Discrete Joint Generative Framework for Tabular Data ICML 2025 Transformers from Diffusion: A Unified Framework for Neural Message Passing JMLR 2025 Graph Out-of-Distribution Detection Goes Neighborhood Shaping ICML 2024 How Graph Neural Networks Learn: Lessons from Training Dynamics ICML 2024 Learning Divergence Fields for Shift-Robust Graph Representations ICML 2024 TDeLTA: A Light-Weight and Robust Table Detection Method Based on Learning Text Arrangement AAAI 2024 DIFFormer: Scalable (Graph) Transformers Induced by Energy Constrained Diffusion ICLR 2023 Energy-based Out-of-Distribution Detection for Graph Neural Networks ICLR 2023 Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs ICLR 2023 SGFormer: Simplifying and Empowering Transformers for Large-Graph Representations NeurIPS 2023 Unleashing the Power of Graph Data Augmentation on Covariate Distribution Shift NeurIPS 2023 Geometric Knowledge Distillation: Topology Compression for Graph Neural Networks NeurIPS 2022 GraphDE: A Generative Framework for Debiased Learning and Out-of-Distribution Detection on Graphs NeurIPS 2022 Handling Distribution Shifts on Graphs: An Invariance Perspective ICLR 2022 Learning Substructure Invariance for Out-of-Distribution Molecular Representations NeurIPS 2022 NodeFormer: A Scalable Graph Structure Learning Transformer for Node Classification NeurIPS 2022 Towards Out-of-Distribution Sequential Event Prediction: A Causal Treatment NeurIPS 2022 Trading Hard Negatives and True Negatives: A Debiased Contrastive Collaborative Filtering Approach IJCAI 2022 Bridging Explicit and Implicit Deep Generative Models via Neural Stein Estimators NeurIPS 2021 From Canonical Correlation Analysis to Self-supervised Graph Neural Networks NeurIPS 2021 Towards Open-World Feature Extrapolation: An Inductive Graph Learning Approach NeurIPS 2021 Towards Open-World Recommendation: An Inductive Model-based Collaborative Filtering Approach ICML 2021 Feature Evolution Based Multi-Task Learning for Collaborative Filtering with Social Trust IJCAI 2019 Learning Latent Process from High-Dimensional Event Sequences via Efficient Sampling NeurIPS 2019