Pan Li - RankMe

194 papers A* 60A 5B 3Misc 1Journal 119Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Survey of Deep Graph Learning under Distribution Shifts: From Graph Out-of-Distribution Generalization to Adaptation. ACM Trans. Knowl. Discov. Data Kexin Zhang, Shuhan Liu, Song Wang, Weili Shi, Chen Chen, Pan Li, Sheng Li, Jundong Li, Kaize Ding
2026	J	`jnl`	Accelerated Sequential Flow Matching: A Bayesian Filtering Perspective. CoRR Yinan Huang, Hans Hao-Hsun Hsu, Junran Wang, Bo Dai, Pan Li
2026	J	`jnl`	Beyond Test-Time Training: Learning to Reason via Hardware-Efficient Optimal Control. CoRR Peihao Wang, Shan Yang, Xijun Wang, Tesi Xiao, Xin Liu, Changlong Yu, Yu Lou, Pan Li, Zhangyang Wang, Ming Lin, René Vidal
2026	J	`jnl`	GRIP: Algorithm-Agnostic Machine Unlearning for Mixture-of-Experts via Geometric Router Constraints. CoRR Andy Zhu, Rongzhe Wei, Yupu Gu, Pan Li
2026	J	`jnl`	MoEEdit: Efficient and Routing-Stable Knowledge Editing for Mixture-of-Experts LLMs. CoRR Yupu Gu, Rongzhe Wei, Andy Zhu, Pan Li
2026	J	`jnl`	On Information Self-Locking in Reinforcement Learning for Active Reasoning of LLM agents. CoRR Deyu Zou, Yongqiang Chen, Fan Feng, Mufei Li, Pan Li, Yu Gong, James Cheng
2026	J	`jnl`	ParamMem: Augmenting Language Agents with Parametric Reflective Memory. CoRR Tianjun Yao, Yongqiang Chen, Yujia Zheng, Pan Li, Zhiqiang Shen, Kun Zhang
2026	J	`jnl`	Scalable Spatio-Temporal SE(3) Diffusion for Long-Horizon Protein Dynamics. CoRR Nima Shoghi, Yuxuan Liu, Yuning Shen, Rob Brekelmans, Pan Li, Quanquan Gu
2026	A*	`conf`	Towards A Universal Graph Structural Encoder. WWW Jialin Chen, Haolan Zuo, Haoyu Wang, Siqi Miao, Pan Li, Rex Ying
2026	J	`jnl`	∇-Reasoner: LLM Reasoning via Test-Time Gradient Descent in Latent Space. CoRR Peihao Wang, Ruisi Cai, Zhen Wang, Hongyuan Mei, Qiang Liu, Pan Li, Zhangyang Wang
2025	J	`jnl`	Branching Strategies Based on Subgraph GNNs: A Study on Theoretical Promise versus Practical Reality. CoRR Junru Zhou, Yicheng Wang, Pan Li
2025	A*	`conf`	Convergent Privacy Loss of Noisy-SGD without Convexity and Smoothness. ICLR Eli Chien, Pan Li
2025	J	`jnl`	Differentially Private Relational Learning with Entity-level Privacy Guarantees. CoRR Yinan Huang, Haoteng Yin, Eli Chien, Rongzhe Wei, Pan Li
2025	J	`jnl`	Do LLMs Really Forget? Evaluating Unlearning with Knowledge Correlation and Confidence Awareness. CoRR Rongzhe Wei, Peizhi Niu, Hans Hao-Hsun Hsu, Ruihan Wu, Haoteng Yin, Mohsen Ghassemi, Yifan Li, Vamsi K. Potluru, Eli Chien, Kamalika Chaudhuri, Olgica Milenkovic, Pan Li
2025	A*	`conf`	Generalization Principles for Inference over Text-Attributed Graphs with Large Language Models. ICML Haoyu Peter Wang, Shikun Liu, Rongzhe Wei, Pan Li
2025	J	`jnl`	Graph-KV: Breaking Sequence via Injecting Structural Biases into Large Language Models. CoRR Haoyu Wang, Peihao Wang, Mufei Li, Shikun Liu, Siqi Miao, Zhangyang Wang, Pan Li
2025	J	`jnl`	Improving Graph Neural Networks on Multi-node Tasks with the Labeling Trick. J. Mach. Learn. Res. Xiyuan Wang, Pan Li, Muhan Zhang
2025	A*	`conf`	LayerDAG: A Layerwise Autoregressive Diffusion Model for Directed Acyclic Graph Generation. ICLR Mufei Li, Viraj Shitole, Eli Chien, Changhai Man, Zhaodong Wang, Srinivas, Ying Zhang, Tushar Krishna, Pan Li
2025	J	`jnl`	Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering. CoRR Tianjun Yao, Haoxuan Li, Zhiqiang Shen, Pan Li, Tongliang Liu, Kun Zhang
2025	J	`jnl`	Locality-Sensitive Hashing-Based Efficient Point Transformer for Charged Particle Reconstruction. CoRR Shitij Govil, Jack P. Rodgers, Yuan-Tang Chou, Siqi Miao, Amit Saha, Advaith Anand, Kilian Lieret, Gage DeZoort, Mia Liu, Javier M. Duarte, Pan Li, Shih-Chieh Hsu
2025	J	`jnl`	MatterTune: An Integrated, User-Friendly Platform for Fine-Tuning Atomistic Foundation Models to Accelerate Materials Simulation and Discovery. CoRR Lingyu Kong, Nima Shoghi, Guoxiang Hu, Pan Li, Victor Fung
2025	J	`jnl`	Model Generalization on Text Attribute Graphs: Principles with Large Language Models. CoRR Haoyu Wang, Shikun Liu, Rongzhe Wei, Pan Li
2025	J	`jnl`	Powers of Magnetic Graph Matrix: Fourier Spectrum, Walk Compression, and Applications. CoRR Yinan Huang, David F. Gleich, Pan Li
2025	J	`jnl`	Privacy Amplification in Differentially Private Zeroth-Order Optimization with Hidden States. CoRR Eli Chien, Wei-Ning Chen, Pan Li
2025	A*	`conf`	Rethinking Addressing in Language Models via Contextualized Equivariant Positional Encoding. ICML Jiajun Zhu, Peihao Wang, Ruisi Cai, Jason D. Lee, Pan Li, Zhangyang Wang
2025	J	`jnl`	Rethinking Addressing in Language Models via Contexualized Equivariant Positional Encoding. CoRR Jiajun Zhu, Peihao Wang, Ruisi Cai, Jason D. Lee, Pan Li, Zhangyang Wang
2025	J	`jnl`	RoFt-Mol: Benchmarking Robust Fine-Tuning with Molecular Graph Foundation Models. CoRR Shikun Liu, Deyu Zou, Nima Shoghi, Victor Fung, Kai Liu, Pan Li
2025	A*	`conf`	Simple is Effective: The Roles of Graphs and Large Language Models in Knowledge-Graph-Based Retrieval-Augmented Generation. ICLR Mufei Li, Siqi Miao, Pan Li
2025	J	`jnl`	Structural Alignment Improves Graph Test-Time Adaptation. CoRR Hans Hao-Hsun Hsu, Shikun Liu, Han Zhao, Pan Li
2025	J	`jnl`	The Trojan Knowledge: Bypassing Commercial LLM Guardrails via Harmless Prompt Weaving and Adaptive Tree Search. CoRR Rongzhe Wei, Peizhi Niu, Xinjie Shen, Tony Tu, Yifan Li, Ruihan Wu, Eli Chien, Pin-Yu Chen, Olgica Milenkovic, Pan Li
2025	J	`jnl`	Towards A Universal Graph Structural Encoder. CoRR Jialin Chen, Haolan Zuo, Haoyu Peter Wang, Siqi Miao, Pan Li, Rex Ying
2025	—	`conf`	Towards Universal Debiasing for Language Models-based Tabular Data Generation. EMNLP (Findings) Tianchun Li, Tianci Liu, Xingchen Wang, Rongzhe Wei, Pan Li, Lu Su, Jing Gao
2025	J	`jnl`	Towards Universal Debiasing for Language Models-based Tabular Data Generation. CoRR Tianchun Li, Tianci Liu, Xingchen Wang, Rongzhe Wei, Pan Li, Lu Su, Jing Gao
2025	J	`jnl`	Towards unveiling sensitive and decisive patterns in explainable AI with a case study in geometric deep learning. Nat. Mac. Intell. Jiajun Zhu, Siqi Miao, Rex Ying, Pan Li
2025	A*	`conf`	Unbiased Recommender Learning from Implicit Feedback via Weakly Supervised Learning. ICML Hao Wang, Zhichao Chen, Haotian Wang, Yanchao Tan, Pan Li, Tianqiao Liu, Xu Chen, Haoxuan Li, Zhouchen Lin
2025	A*	`conf`	Underestimated Privacy Risks for Minority Populations in Large Language Model Unlearning. ICML Rongzhe Wei, Mufei Li, Mohsen Ghassemi, Eleonora Kreacic, Yifan Li, Xiang Yue, Bo Li, Vamsi K. Potluru, Pan Li, Eli Chien
2025	A*	`conf`	Understanding and Mitigating Bottlenecks of State Space Models through the Lens of Recency and Over-smoothing. ICLR Peihao Wang, Ruisi Cai, Yuehao Wang, Jiajun Zhu, Pragya Srivastava, Zhangyang Wang, Pan Li
2025	J	`jnl`	Understanding and Mitigating Bottlenecks of State Space Models through the Lens of Recency and Over-smoothing. CoRR Peihao Wang, Ruisi Cai, Yuehao Wang, Jiajun Zhu, Pragya Srivastava, Zhangyang Wang, Pan Li
2025	J	`jnl`	Weak-to-Strong GraphRAG: Aligning Weak Retrievers with Large Language Models for Graph-based Retrieval Augmented Generation. CoRR Deyu Zou, Yongqiang Chen, Mufei Li, Siqi Miao, Chenxi Liu, Bo Han, James Cheng, Pan Li
2025	A*	`conf`	What Are Good Positional Encodings for Directed Graphs? ICLR Yinan Huang, Haoyu Peter Wang, Pan Li
2024	J	`jnl`	A Benchmark on Directed Graph Representation Learning in Hardware Designs. CoRR Haoyu Wang, Yinan Huang, Nan Wu, Pan Li
2024	J	`jnl`	A Survey of Deep Graph Learning under Distribution Shifts: from Graph Out-of-Distribution Generalization to Adaptation. CoRR Kexin Zhang, Shuhan Liu, Song Wang, Weili Shi, Chen Chen, Pan Li, Sheng Li, Jundong Li, Kaize Ding
2024	J	`jnl`	Ambiguities in neural-network-based hyperedge prediction. J. Appl. Comput. Topol. Changlin Wan, Muhan Zhang, Pengtao Dang, Wei Hao, Sha Cao, Pan Li, Chi Zhang
2024	A*	`conf`	Certified Machine Unlearning via Noisy Stochastic Gradient Descent. NeurIPS Eli Chien, Haoyu Wang, Ziang Chen, Pan Li
2024	J	`jnl`	Convergent Privacy Loss of Noisy-SGD without Convexity and Smoothness. CoRR Eli Chien, Pan Li
2024	J	`jnl`	DIG-MILP: a Deep Instance Generator for Mixed-Integer Linear Programming with Feasibility Guarantee. Trans. Mach. Learn. Res. Haoyu Peter Wang, Jialin Liu, Xiaohan Chen, Xinshang Wang, Pan Li, Wotao Yin
2024	A*	`conf`	Differentially Private Graph Diffusion with Applications in Personalized PageRanks. NeurIPS Rongzhe Wei, Eli Chien, Pan Li
2024	J	`jnl`	Differentially Private Graph Diffusion with Applications in Personalized PageRanks. CoRR Rongzhe Wei, Eli Chien, Pan Li
2024	J	`jnl`	Distance Information Improves Heterogeneous Graph Neural Networks. IEEE Trans. Knowl. Data Eng. Chuan Shi, Houye Ji, Zhiyuan Lu, Ye Tang, Pan Li, Cheng Yang
2024	A	`conf`	GAD-NR: Graph Anomaly Detection via Neighborhood Reconstruction. WSDM Amit Roy, Juan Shu, Jia Li, Carl Yang, Olivier Elshocht, Jeroen Smeets, Pan Li
2024	A*	`conf`	GeSS: Benchmarking Geometric Deep Learning under Scientific Applications with Distribution Shifts. NeurIPS Deyu Zou, Shikun Liu, Siqi Miao, Victor Fung, Shiyu Chang, Pan Li
2024	A*	`conf`	Graph As Point Set. ICML Xiyuan Wang, Pan Li, Muhan Zhang
2024	J	`jnl`	Graph as Point Set. CoRR Xiyuan Wang, Pan Li, Muhan Zhang
2024	J	`jnl`	GraphMaker: Can Diffusion Models Generate Large Attributed Graphs? Trans. Mach. Learn. Res. Mufei Li, Eleonora Kreacic, Vamsi K. Potluru, Pan Li
2024	A*	`conf`	Langevin Unlearning: A New Perspective of Noisy Gradient Descent for Machine Unlearning. NeurIPS Eli Chien, Haoyu Wang, Ziang Chen, Pan Li
2024	J	`jnl`	Langevin Unlearning: A New Perspective of Noisy Gradient Descent for Machine Unlearning. CoRR Eli Chien, Haoyu Wang, Ziang Chen, Pan Li
2024	J	`jnl`	LayerDAG: A Layerwise Autoregressive Diffusion Model for Directed Acyclic Graph Generation. CoRR Mufei Li, Viraj Shitole, Eli Chien, Changhai Man, Zhaodong Wang, Srinivas Sridharan, Ying Zhang, Tushar Krishna, Pan Li
2024	A*	`conf`	Learning Scalable Structural Representations for Link Prediction with Bloom Signatures. WWW Tianyi Zhang, Haoteng Yin, Rongzhe Wei, Pan Li, Anshumali Shrivastava
2024	A*	`conf`	Locality-Sensitive Hashing-Based Efficient Point Transformer with Applications in High-Energy Physics. ICML Siqi Miao, Zhiyuan Lu, Mia Liu, Javier M. Duarte, Pan Li
2024	J	`jnl`	Locality-Sensitive Hashing-Based Efficient Point Transformer with Applications in High-Energy Physics. CoRR Siqi Miao, Zhiyuan Lu, Mia Liu, Javier M. Duarte, Pan Li
2024	J	`jnl`	No Need to Look Back: An Efficient and Scalable Approach for Temporal Network Representation Learning. CoRR Yuhong Luo, Pan Li
2024	J	`jnl`	On the Inherent Privacy Properties of Discrete Denoising Diffusion Models. Trans. Mach. Learn. Res. Rongzhe Wei, Eleonora Kreacic, Haoyu Peter Wang, Haoteng Yin, Eli Chien, Vamsi K. Potluru, Pan Li
2024	A*	`conf`	On the Stability of Expressive Positional Encodings for Graphs. ICLR Yinan Huang, William Lu, Joshua Robinson, Yu Yang, Muhan Zhang, Stefanie Jegelka, Pan Li
2024	A*	`conf`	Pairwise Alignment Improves Graph Domain Adaptation. ICML Shikun Liu, Deyu Zou, Han Zhao, Pan Li
2024	J	`jnl`	Pairwise Alignment Improves Graph Domain Adaptation. CoRR Shikun Liu, Deyu Zou, Han Zhao, Pan Li
2024	A*	`conf`	Polynomial Width is Sufficient for Set Representation with High-dimensional Features. ICLR Peihao Wang, Shenghao Yang, Shu Li, Zhangyang Wang, Pan Li
2024	J	`jnl`	Privately Learning from Graphs with Applications in Fine-tuning Large Language Models. CoRR Haoteng Yin, Rongzhe Wei, Eli Chien, Pan Li
2024	—	`conf`	Scalable and Efficient Temporal Graph Representation Learning via Forward Recent Sampling. LoG Yuhong Luo, Pan Li
2024	J	`jnl`	Simple is Effective: The Roles of Graphs and Large Language Models in Knowledge-Graph-Based Retrieval-Augmented Generation. CoRR Mufei Li, Siqi Miao, Pan Li
2024	J	`jnl`	Stochastic Gradient Langevin Unlearning. CoRR Eli Chien, Haoyu Wang, Ziang Chen, Pan Li
2024	A*	`conf`	Towards Poisoning Fair Representations. ICLR Tianci Liu, Haoyu Wang, Feijie Wu, Hengtong Zhang, Pan Li, Lu Su, Jing Gao
2024	J	`jnl`	Towards Stable, Globally Expressive Graph Representations with Laplacian Eigenvectors. CoRR Junru Zhou, Cai Zhou, Xiyuan Wang, Pan Li, Muhan Zhang
2024	J	`jnl`	Towards Understanding Sensitive and Decisive Patterns in Explainable AI: A Case Study of Model Interpretation in Geometric Deep Learning. CoRR Jiajun Zhu, Siqi Miao, Rex Ying, Pan Li
2024	J	`jnl`	Underestimated Privacy Risks for Minority Populations in Large Language Model Unlearning. CoRR Rongzhe Wei, Mufei Li, Mohsen Ghassemi, Eleonora Kreacic, Yifan Li, Xiang Yue, Bo Li, Vamsi K. Potluru, Pan Li, Eli Chien
2024	J	`jnl`	What Can We Learn from State Space Models for Machine Learning on Graphs? CoRR Yinan Huang, Siqi Miao, Pan Li
2023	J	`jnl`	ABKD: Graph Neural Network Compression with Attention-Based Knowledge Distillation. CoRR Anshul Ahluwalia, Rohit Das, Payman Behnam, Alind Khare, Pan Li, Alexey Tumanov
2023	J	`jnl`	DIG-MILP: a Deep Instance Generator for Mixed-Integer Linear Programming with Feasibility Guarantee. CoRR Haoyu Wang, Jialin Liu, Xiaohan Chen, Xinshang Wang, Pan Li, Wotao Yin
2023	A*	`conf`	Differentially Private Decoupled Graph Convolutions for Multigranular Topology Protection. NeurIPS Eli Chien, Wei-Ning Chen, Chao Pan, Pan Li, Ayfer Özgür, Olgica Milenkovic
2023	J	`jnl`	Differentially Private Decoupled Graph Convolutions for Multigranular Topology Protection. CoRR Eli Chien, Wei-Ning Chen, Chao Pan, Pan Li, Ayfer Özgür, Olgica Milenkovic
2023	A*	`conf`	Equivariant Hypergraph Diffusion Neural Operators. ICLR Peihao Wang, Shenghao Yang, Yunyu Liu, Zhangyang Wang, Pan Li
2023	A*	`conf`	Expressive and Efficient Representation Learning for Ranking Links in Temporal Graphs. WWW Susheel Suresh, Mayank Shrivastava, Arko Mukherjee, Jennifer Neville, Pan Li
2023	A*	`conf`	Extensible and Efficient Proxy for Neural Architecture Search. ICCV Yuhong Li, Jiajie Li, Cong Hao, Pan Li, Jinjun Xiong, Deming Chen
2023	J	`jnl`	GAD-NR: Graph Anomaly Detection via Neighborhood Reconstruction. CoRR Amit Roy, Juan Shu, Jia Li, Carl Yang, Olivier Elshocht, Jeroen Smeets, Pan Li
2023	J	`jnl`	GDL-DS: A Benchmark for Geometric Deep Learning under Distribution Shifts. CoRR Deyu Zou, Shikun Liu, Siqi Miao, Victor Fung, Shiyu Chang, Pan Li
2023	J	`jnl`	GraphMaker: Can Diffusion Models Generate Large Attributed Graphs? CoRR Mufei Li, Eleonora Kreacic, Vamsi K. Potluru, Pan Li
2023	J	`jnl`	High Pileup Particle Tracking with Object Condensation. CoRR Kilian Lieret, Gage DeZoort, Devdoot Chatterjee, Jian Park, Siqi Miao, Pan Li
2023	J	`jnl`	Improving Graph Neural Networks on Multi-node Tasks with Labeling Tricks. CoRR Xiyuan Wang, Pan Li, Muhan Zhang
2023	A*	`conf`	Interpretable Geometric Deep Learning via Learnable Randomness Injection. ICLR Siqi Miao, Yunan Luo, Mia Liu, Pan Li
2023	J	`jnl`	Learning Scalable Structural Representations for Link Prediction with Bloom Signatures. CoRR Tianyi Zhang, Haoteng Yin, Rongzhe Wei, Pan Li, Anshumali Shrivastava
2023	J	`jnl`	On the Inherent Privacy Properties of Discrete Denoising Diffusion Models. CoRR Rongzhe Wei, Eleonora Kreacic, Haoyu Wang, Haoteng Yin, Eli Chien, Vamsi K. Potluru, Pan Li
2023	J	`jnl`	On the Stability of Expressive Positional Encodings for Graph Neural Networks. CoRR Yinan Huang, William Lu, Joshua Robinson, Yu Yang, Muhan Zhang, Stefanie Jegelka, Pan Li
2023	J	`jnl`	Polynomial Width is Sufficient for Set Representation with High-dimensional Features. CoRR Peihao Wang, Shenghao Yang, Shu Li, Zhangyang Wang, Pan Li
2023	J	`jnl`	SUREL+: Moving from Walks to Sets for Scalable Subgraph-based Graph Representation Learning. CoRR Haoteng Yin, Muhan Zhang, Jianguo Wang, Pan Li
2023	J	`jnl`	SUREL+: Moving from Walks to Sets for Scalable Subgraph-based Graph Representation Learning. Proc. VLDB Endow. Haoteng Yin, Muhan Zhang, Jianguo Wang, Pan Li
2023	A*	`conf`	Structural Re-weighting Improves Graph Domain Adaptation. ICML Shikun Liu, Tianchun Li, Yongbin Feng, Nhan Tran, Han Zhao, Qiang Qiu, Pan Li
2023	J	`jnl`	Structural Re-weighting Improves Graph Domain Adaptation. CoRR Shikun Liu, Tianchun Li, Yongbin Feng, Nhan Tran, Han Zhao, Qiang Qiu, Pan Li
2023	J	`jnl`	Towards Poisoning Fair Representations. CoRR Tianci Liu, Haoyu Wang, Feijie Wu, Hengtong Zhang, Pan Li, Lu Su, Jing Gao
2023	A*	`conf`	Unsupervised Learning for Combinatorial Optimization Needs Meta Learning. ICLR Haoyu Peter Wang, Pan Li
2022	A*	`conf`	4SDrug: Symptom-based Set-to-set Small and Safe Drug Recommendation. KDD Yanchao Tan, Chengjun Kong, Leisheng Yu, Pan Li, Chaochao Chen, Xiaolin Zheng, Vicki Hertzberg, Carl Yang
2022	J	`jnl`	Algorithm and System Co-design for Efficient Subgraph-based Graph Representation Learning. CoRR Haoteng Yin, Muhan Zhang, Yanbang Wang, Jianguo Wang, Pan Li
2022	J	`jnl`	Algorithm and System Co-design for Efficient Subgraph-based Graph Representation Learning. Proc. VLDB Endow. Haoteng Yin, Muhan Zhang, Yanbang Wang, Jianguo Wang, Pan Li
2022	J	`jnl`	Equivariant Hypergraph Diffusion Neural Operators. CoRR Peihao Wang, Shenghao Yang, Yunyu Liu, Zhangyang Wang, Pan Li
2022	A*	`conf`	Equivariant and Stable Positional Encoding for More Powerful Graph Neural Networks. ICLR Haorui Wang, Haoteng Yin, Muhan Zhang, Pan Li
2022	J	`jnl`	Equivariant and Stable Positional Encoding for More Powerful Graph Neural Networks. CoRR Haorui Wang, Haoteng Yin, Muhan Zhang, Pan Li
2022	J	`jnl`	Extensible Proxy for Efficient NAS. CoRR Yuhong Li, Jiajie Li, Cong Han, Pan Li, Jinjun Xiong, Deming Chen
2022	J	`jnl`	Federated Graph Representation Learning using Self-Supervision. CoRR Susheel Suresh, Danny Godbout, Arko Mukherjee, Mayank Shrivastava, Jennifer Neville, Pan Li
2022	J	`jnl`	Graph Auto-Encoder Via Neighborhood Wasserstein Reconstruction. CoRR Mingyue Tang, Carl Yang, Pan Li
2022	A*	`conf`	Graph Auto-Encoder via Neighborhood Wasserstein Reconstruction. ICLR Mingyue Tang, Pan Li, Carl Yang
2022	J	`jnl`	Graph Federated Learning with Hidden Representation Sharing. CoRR Shuang Wu, Mingxuan Zhang, Yuantong Li, Carl Yang, Pan Li
2022	J	`jnl`	High-Level Synthesis Performance Prediction using GNNs: Benchmarking, Modeling, and Advancing. CoRR Nan Wu, Hang Yang, Yuan Xie, Pan Li, Cong Hao
2022	A*	`conf`	High-level synthesis performance prediction using GNNs: benchmarking, modeling, and advancing. DAC Nan Wu, Hang Yang, Yuan Xie, Pan Li, Cong Hao
2022	J	`jnl`	Interpretable Geometric Deep Learning via Learnable Randomness Injection. CoRR Siqi Miao, Yunan Luo, Mia Liu, Pan Li
2022	A*	`conf`	Interpretable and Generalizable Graph Learning via Stochastic Attention Mechanism. ICML Siqi Miao, Mia Liu, Pan Li
2022	J	`jnl`	Interpretable and Generalizable Graph Learning via Stochastic Attention Mechanism. CoRR Siqi Miao, Miaoyuan Liu, Pan Li
2022	J	`jnl`	MobilePrune: Neural Network Compression via ℓ0 Sparse Group Lasso on the Mobile System. Sensors Yubo Shao, Kaikai Zhao, Zhiwen Cao, Zhehao Peng, Xingang Peng, Pan Li, Yijie Wang, Jianzhu Ma
2022	—	`conf`	Neighborhood-Aware Scalable Temporal Network Representation Learning. LoG Yuhong Luo, Pan Li
2022	J	`jnl`	Neighborhood-aware Scalable Temporal Network Representation Learning. CoRR Yuhong Luo, Pan Li
2022	A*	`conf`	Neural Predicting Higher-order Patterns in Temporal Networks. WWW Yunyu Liu, Jianzhu Ma, Pan Li
2022	A	`conf`	On Positional and Structural Node Features for Graph Neural Networks on Non-attributed Graphs. CIKM Hejie Cui, Zijie Lu, Pan Li, Carl Yang
2022	J	`jnl`	Two-Dimensional Weisfeiler-Lehman Graph Neural Networks for Link Prediction. CoRR Yang Hu, Xiyuan Wang, Zhouchen Lin, Pan Li, Muhan Zhang
2022	A*	`conf`	Understanding Non-linearity in Graph Neural Networks from the Bayesian-Inference Perspective. NeurIPS Rongzhe Wei, Haoteng Yin, Junteng Jia, Austin R. Benson, Pan Li
2022	J	`jnl`	Understanding Non-linearity in Graph Neural Networks from the Bayesian-Inference Perspective. CoRR Rongzhe Wei, Haoteng Yin, Junteng Jia, Austin R. Benson, Pan Li
2022	A*	`conf`	Unsupervised Learning for Combinatorial Optimization with Principled Objective Relaxation. NeurIPS Haoyu Wang, Nan Wu, Hang Yang, Cong Hao, Pan Li
2022	J	`jnl`	Unsupervised Learning for Combinatorial Optimization with Principled Objective Relaxation. CoRR Haoyu Wang, Nan Wu, Hang Yang, Cong Hao, Pan Li
2021	A*	`conf`	Adaptive Universal Generalized PageRank Graph Neural Network. ICLR Eli Chien, Jianhao Peng, Pan Li, Olgica Milenkovic
2021	A*	`conf`	Adversarial Graph Augmentation to Improve Graph Contrastive Learning. NeurIPS Susheel Suresh, Pan Li, Cong Hao, Jennifer Neville
2021	J	`jnl`	Adversarial Graph Augmentation to Improve Graph Contrastive Learning. CoRR Susheel Suresh, Pan Li, Cong Hao, Jennifer Neville
2021	J	`jnl`	Applications and Techniques for Fast Machine Learning in Science. CoRR Allison McCarn Deiana, Nhan Tran, Joshua Agar, Michaela Blott, Giuseppe Di Guglielmo, Javier M. Duarte, Philip C. Harris, Scott Hauck, Mia Liu, Mark S. Neubauer, Jennifer Ngadiuba, Seda Ogrenci Memik, Maurizio Pierini, Thea Aarrestad, Steffen Bähr, Jürgen Becker, Anne-Sophie Berthold, Richard J. Bonventre, Tomás E. Müller-Bravo, Markus Diefenthaler, Zhen Dong, Nick Fritzsche, Amir Gholami, Ekaterina Govorkova, Kyle J. Hazelwood, Christian Herwig, Babar Khan, Sehoon Kim, Thomas Klijnsma, Yaling Liu, Kin Ho Lo, Tri Nguyen, Gianantonio Pezzullo, Seyedramin Rasoulinezhad, Ryan A. Rivera, Kate Scholberg, Justin Selig, Sougata Sen, Dmitri Strukov, William Tang, Savannah Thais, Kai Lukas Unger, Ricardo Vilalta, Belinavon Krosigk, Thomas K. Warburton, Maria Acosta Flechas, Anthony Aportela, Thomas Calvet, Leonardo Cristella, Daniel Diaz, Caterina Doglioni, Maria Domenica Galati, Elham E Khoda, Farah Fahim, Davide Giri, Benjamin Hawks, Duc Hoang, Burt Holzman, Shih-Chieh Hsu, Sergo Jindariani, Iris Johnson, Raghav Kansal, Ryan Kastner, Erik Katsavounidis, Jeffrey D. Krupa, Pan Li, Sandeep Madireddy, Ethan Marx, Patrick McCormack, Andres Meza, Jovan Mitrevski, Mohammed Attia Mohammed, Farouk Mokhtar, Eric A. Moreno, Srishti Nagu, Rohin Narayan, Noah Palladino, Zhiqiang Que, Sang Eon Park, Subramanian Ramamoorthy, Dylan S. Rankin, Simon Rothman, Ashish Sharma, Sioni Summers, Pietro Vischia, Jean-Roch Vlimant, Olivia Weng
2021	A*	`conf`	Bipartite Dynamic Representations for Abuse Detection. KDD Andrew Z. Wang, Rex Ying, Pan Li, Nikhil Rao, Karthik Subbian, Jure Leskovec
2021	A*	`conf`	Breaking the Limit of Graph Neural Networks by Improving the Assortativity of Graphs with Local Mixing Patterns. KDD Susheel Suresh, Vinith Budde, Jennifer Neville, Pan Li, Jianzhu Ma
2021	J	`jnl`	Breaking the Limit of Graph Neural Networks by Improving the Assortativity of Graphs with Local Mixing Patterns. CoRR Susheel Suresh, Vinith Budde, Jennifer Neville, Pan Li, Jianzhu Ma
2021	A	`conf`	F-FADE: Frequency Factorization for Anomaly Detection in Edge Streams. WSDM Yen-Yu Chang, Pan Li, Rok Sosic, M. H. Afifi, Marco Schweighauser, Jure Leskovec
2021	A*	`conf`	Generic Neural Architecture Search via Regression. NeurIPS Yuhong Li, Cong Hao, Pan Li, Jinjun Xiong, Deming Chen
2021	J	`jnl`	Generic Neural Architecture Search via Regression. CoRR Yuhong Li, Cong Hao, Pan Li, Jinjun Xiong, Deming Chen
2021	A*	`conf`	Heterogeneous Graph Neural Network with Distance Encoding. ICDM Houye Ji, Cheng Yang, Chuan Shi, Pan Li
2021	A*	`conf`	Inductive Representation Learning in Temporal Networks via Causal Anonymous Walks. ICLR Yanbang Wang, Yen-Yu Chang, Yunyu Liu, Jure Leskovec, Pan Li
2021	J	`jnl`	Inductive Representation Learning in Temporal Networks via Causal Anonymous Walks. CoRR Yanbang Wang, Yen-Yu Chang, Yunyu Liu, Jure Leskovec, Pan Li
2021	A*	`conf`	Labeling Trick: A Theory of Using Graph Neural Networks for Multi-Node Representation Learning. NeurIPS Muhan Zhang, Pan Li, Yinglong Xia, Kai Wang, Long Jin
2021	B	`conf`	Landing Probabilities of Random Walks for Seed-Set Expansion in Hypergraphs. ITW Eli Chien, Pan Li, Olgica Milenkovic
2021	A*	`conf`	Local Hyper-Flow Diffusion. NeurIPS Kimon Fountoulakis, Pan Li, Shenghao Yang
2021	J	`jnl`	Local Hyper-flow Diffusion. CoRR Kimon Fountoulakis, Pan Li, Shenghao Yang
2021	A*	`conf`	MELOPPR: Software/Hardware Co-design for Memory-efficient Low-latency Personalized PageRank. DAC Lixiang Li, Yao Chen, Zacharie Zirnheld, Pan Li, Cong Hao
2021	J	`jnl`	MELOPPR: Software/Hardware Co-design for Memory-efficient Low-latency Personalized PageRank. CoRR Lixiang Li, Yao Chen, Zacharie Zirnheld, Pan Li, Cong Hao
2021	A*	`conf`	MStream: Fast Anomaly Detection in Multi-Aspect Streams. WWW Siddharth Bhatia, Arjit Jain, Pan Li, Ritesh Kumar, Bryan Hooi
2021	A*	`conf`	Nested Graph Neural Networks. NeurIPS Muhan Zhang, Pan Li
2021	J	`jnl`	Nested Graph Neural Networks. CoRR Muhan Zhang, Pan Li
2021	J	`jnl`	Neural Higher-order Pattern (Motif) Prediction in Temporal Networks. CoRR Yunyu Liu, Jianzhu Ma, Pan Li
2021	J	`jnl`	On Positional and Structural Node Features for Graph Neural Networks on Non-attributed Graphs. CoRR Hejie Cui, Zijie Lu, Pan Li, Carl Yang
2021	J	`jnl`	Principled Hyperedge Prediction with Structural Spectral Features and Neural Networks. CoRR Changlin Wan, Muhan Zhang, Wei Hao, Sha Cao, Pan Li, Chi Zhang
2021	J	`jnl`	Program-to-Circuit: Exploiting GNNs for Program Representation and Circuit Translation. CoRR Nan Wu, Huake He, Yuan Xie, Pan Li, Cong Hao
2021	A*	`conf`	Strongly Local Hypergraph Diffusions for Clustering and Semi-supervised Learning. WWW Meng Liu, Nate Veldt, Haoyu Song, Pan Li, David F. Gleich
2021	A*	`conf`	TEDIC: Neural Modeling of Behavioral Patterns in Dynamic Social Interaction Networks. WWW Yanbang Wang, Pan Li, Chongyang Bai, Jure Leskovec
2020	J	`jnl`	Distance Encoding - Design Provably More Powerful Graph Neural Networks for Structural Representation Learning. CoRR Pan Li, Yanbang Wang, Hongwei Wang, Jure Leskovec
2020	A*	`conf`	Distance Encoding: Design Provably More Powerful Neural Networks for Graph Representation Learning. NeurIPS Pan Li, Yanbang Wang, Hongwei Wang, Jure Leskovec
2020	J	`jnl`	F-FADE: Frequency Factorization for Anomaly Detection in Edge Streams. CoRR Yen-Yu Chang, Pan Li, Rok Sosic, M. H. Afifi, Marco Schweighauser, Jure Leskovec
2020	A*	`conf`	Graph Information Bottleneck. NeurIPS Tailin Wu, Hongyu Ren, Pan Li, Jure Leskovec
2020	J	`jnl`	Graph Information Bottleneck. CoRR Tailin Wu, Hongyu Ren, Pan Li, Jure Leskovec
2020	J	`jnl`	Joint Adaptive Feature Smoothing and Topology Extraction via Generalized PageRank GNNs. CoRR Eli Chien, Jianhao Peng, Pan Li, Olgica Milenkovic
2020	J	`jnl`	MStream: Fast Streaming Multi-Aspect Group Anomaly Detection. CoRR Siddharth Bhatia, Arjit Jain, Pan Li, Ritesh Kumar, Bryan Hooi
2020	J	`jnl`	Motif and Hypergraph Correlation Clustering. IEEE Trans. Inf. Theory Pan Li, Gregory J. Puleo, Olgica Milenkovic
2020	J	`jnl`	Quadratic Decomposable Submodular Function Minimization: Theory and Practice. J. Mach. Learn. Res. Pan Li, Niao He, Olgica Milenkovic
2020	J	`jnl`	Revisit graph neural networks and distance encoding in a practical view. CoRR Haoteng Yin, Yanbang Wang, Pan Li
2020	J	`jnl`	Revisiting Graph Neural Networks for Link Prediction. CoRR Muhan Zhang, Pan Li, Yinglong Xia, Kai Wang, Long Jin
2020	J	`jnl`	Strongly Local Hypergraph Diffusions for Clustering and Semi-supervised Learning. CoRR Meng Liu, Nate Veldt, Haoyu Song, Pan Li, David F. Gleich
2019	A*	`conf`	Combining Decision Trees and Neural Networks for Learning-to-Rank in Personal Search. KDD Pan Li, Zhen Qin, Xuanhui Wang, Donald Metzler
2019	A*	`conf`	Conditional Structure Generation through Graph Variational Generative Adversarial Nets. NeurIPS Carl Yang, Peiye Zhuang, Wenhan Shi, Alan Luu, Pan Li
2019	A	`conf`	HS AISTATS I (Eli) Chien, Huozhi Zhou, Pan Li
2019	J	`jnl`	Landing Probabilities of Random Walks for Seed-Set Expansion in Hypergraphs. CoRR Eli Chien, Pan Li, Olgica Milenkovic
2019	—	`—`	Learning on graphs with high-order relations: spectral methods, optimization and applications Pan Li
2019	J	`jnl`	Meta-Graph Based HIN Spectral Embedding: Methods, Analyses, and Insights. CoRR Carl Yang, Yichen Feng, Pan Li, Yu Shi, Jiawei Han
2019	A*	`conf`	Optimizing Generalized PageRank Methods for Seed-Expansion Community Detection. NeurIPS Pan Li, I (Eli) Chien, Olgica Milenkovic
2019	J	`jnl`	Optimizing Generalized PageRank Methods for Seed-Expansion Community Detection. CoRR Pan Li, I (Eli) Chien, Olgica Milenkovic
2019	J	`jnl`	Quadratic Decomposable Submodular Function Minimization: Theory and Practice. CoRR Pan Li, Niao He, Olgica Milenkovic
2018	J	`jnl`	HS CoRR I (Eli) Chien, Huozhi Zhou, Pan Li
2018	A*	`conf`	Meta-Graph Based HIN Spectral Embedding: Methods, Analyses, and Insights. ICDM Carl Yang, Yichen Feng, Pan Li, Yu Shi, Jiawei Han
2018	J	`jnl`	Motif and Hypergraph Correlation Clustering. CoRR Pan Li, Gregory J. Puleo, Olgica Milenkovic
2018	A*	`conf`	Quadratic Decomposable Submodular Function Minimization. NeurIPS Pan Li, Niao He, Olgica Milenkovic
2018	J	`jnl`	Quadratic Decomposable Submodular Function Minimization. CoRR Pan Li, Niao He, Olgica Milenkovic
2018	A*	`conf`	Revisiting Decomposable Submodular Function Minimization with Incidence Relations. NeurIPS Pan Li, Olgica Milenkovic
2018	J	`jnl`	Revisiting Decomposable Submodular Function Minimization with Incidence Relations. CoRR Pan Li, Olgica Milenkovic
2018	A*	`conf`	Submodular Hypergraphs: p-Laplacians, Cheeger Inequalities and Spectral Clustering. ICML Pan Li, Olgica Milenkovic
2018	J	`jnl`	Submodular Hypergraphs: p-Laplacians, Cheeger Inequalities and Spectral Clustering. CoRR Pan Li, Olgica Milenkovic
2017	A	`conf`	Efficient Rank Aggregation via Lehmer Codes. AISTATS Pan Li, Arya Mazumdar, Olgica Milenkovic
2017	J	`jnl`	Efficient Rank Aggregation via Lehmer Codes. CoRR Pan Li, Arya Mazumdar, Olgica Milenkovic
2017	—	`conf`	Inhomogeneous Hypergraph Clustering with Applications. NIPS Pan Li, Olgica Milenkovic
2017	J	`jnl`	Inhomogeneous Hypergraph Clustering with Applications. CoRR Pan Li, Olgica Milenkovic
2017	A*	`conf`	Motif clustering and overlapping clustering for social network analysis. INFOCOM Pan Li, Hoang Dau, Gregory J. Puleo, Olgica Milenkovic
2017	J	`jnl`	Multiclass MinMax Rank Aggregation. CoRR Pan Li, Olgica Milenkovic
2017	B	`conf`	Multiclass MinMax rank aggregation. ISIT Pan Li, Olgica Milenkovic
2016	J	`jnl`	Motif Clustering and Overlapping Clustering for Social Network Analysis. CoRR Pan Li, Son Hoang Dau, Gregory J. Puleo, Olgica Milenkovic
2016	J	`jnl`	Spectrally Efficient CSI Acquisition for Power Line Communications: A Bayesian Compressive Sensing Perspective. IEEE J. Sel. Areas Commun. Wenbo Ding, Yang Lu, Fang Yang, Wei Dai, Pan Li, Sicong Liu, Jian Song
2015	B	`conf`	On recovery of sparse signals with block structures. ISIT Pan Li, Wei Dai, Huadong Meng, Xiqin Wang
2014	—	`conf`	A Feature Selection Method Based on the Sparse Multi-Class SVM for Fingerprinting Localization. VTC Fall Pan Li, Huadong Meng, Xiqin Wang
2013	Misc	`conf`	Hyperparameter-free DOA estimation under power constraints. ICASSP Chundi Zheng, Gang Li, Pan Li, Xiqin Wang