David Wipf - RankMe

81 papers A* 24A 5Misc 1Journal 48Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	No Need to Train Your RDB Foundation Model. CoRR Linjie Xu, Yanlin Zhang, Quan Gan, Minjie Wang, David Wipf
2026	J	`jnl`	RDBLearn: Simple In-Context Prediction Over Relational Databases. CoRR Yanlin Zhang, Linjie Xu, Quan Gan, David Wipf, Minjie Wang
2025	A*	`conf`	Chain-of-Thought Provably Enables Learning the (Otherwise) Unlearnable. ICLR Chenxiao Yang, Zhiyuan Li, David Wipf
2025	A	`conf`	Common Learning Constraints Alter Interpretations of Direct Preference Optimization. AISTATS Lemin Kong, Xiangkun Hu, Tong He, David Wipf
2025	J	`jnl`	Efficient Link Prediction via GNN Layers Induced by Negative Sampling. IEEE Trans. Knowl. Data Eng. Yuxin Wang, Xiannian Hu, Quan Gan, Xuanjing Huang, Xipeng Qiu, David Wipf
2025	A*	`conf`	Explicit Preference Optimization: No Need for an Implicit Reward Model. ICML Xiangkun Hu, Lemin Kong, Tong He, David Wipf
2025	J	`jnl`	Explicit Preference Optimization: No Need for an Implicit Reward Model. CoRR Xiangkun Hu, Lemin Kong, Tong He, David Wipf
2025	A*	`conf`	Griffin: Towards a Graph-Centric Relational Database Foundation Model. ICML Yanbo Wang, Xiyuan Wang, Quan Gan, Minjie Wang, Qibin Yang, David Wipf, Muhan Zhang
2025	J	`jnl`	Griffin: Towards a Graph-Centric Relational Database Foundation Model. CoRR Yanbo Wang, Xiyuan Wang, Quan Gan, Minjie Wang, Qibin Yang, David Wipf, Muhan Zhang
2025	J	`jnl`	Implicit vs Unfolded Graph Neural Networks. J. Mach. Learn. Res. Yongyi Yang, Tang Liu, Yangkun Wang, Zengfeng Huang, David Wipf
2025	J	`jnl`	Learning to Fuse Temporal Proximity Networks: A Case Study in Chimpanzee Social Interactions. CoRR Yixuan He, Aaron Sandel, David Wipf, Mihai Cucuringu, John Mitani, Gesine Reinert
2025	A*	`conf`	MuseGNN: Forming Scalable, Convergent GNN Layers that Minimize a Sampling-Based Energy. ICLR Haitian Jiang, Renjie Liu, Zengfeng Huang, Yichuan Wang, Xiao Yan, Zhenkun Cai, Minjie Wang, David Wipf
2025	J	`jnl`	On Powerful Ways to Generate: Autoregression, Diffusion, and Beyond. CoRR Chenxiao Yang, Cai Zhou, David Wipf, Zhiyuan Li
2025	A	`conf`	Prior-Fitted Networks Scale to Larger Datasets When Treated as Weak Learners. AISTATS Yuxin Wang, Botian Jiang, Yiran Guo, Quan Gan, David Wipf, Xuanjing Huang, Xipeng Qiu
2025	J	`jnl`	Prior-Fitted Networks Scale to Larger Datasets When Treated as Weak Learners. CoRR Yuxin Wang, Botian Jiang, Yiran Guo, Quan Gan, David Wipf, Xuanjing Huang, Xipeng Qiu
2025	A*	`conf`	Sparse Autoencoders, Again? ICML Yin Lu, Xuening Zhu, Tong He, David Wipf
2025	J	`jnl`	Sparse Autoencoders, Again? CoRR Yin Lu, Xuening Zhu, Tong He, David Wipf
2025	J	`jnl`	Synthesize, Retrieve, and Propagate: A Unified Predictive Modeling Framework for Relational Databases. CoRR Ning Li, Kounianhua Du, Han Zhang, Quan Gan, Minjie Wang, David Wipf, Weinan Zhang
2025	J	`jnl`	TaTToo: Tool-Grounded Thinking PRM for Test-Time Scaling in Tabular Reasoning. CoRR Jiaru Zou, Soumya Roy, Vinay Kumar Verma, Ziyi Wang, David Wipf, Pan Lu, Sumit Negi, James Zou, Jingrui He
2025	J	`jnl`	Transformers from Diffusion: A Unified Framework for Neural Message Passing. J. Mach. Learn. Res. Qitian Wu, David Wipf, Junchi Yan
2024	A*	`conf`	4DBInfer: A 4D Benchmarking Toolbox for Graph-Centric Predictive Modeling on RDBs. NeurIPS Minjie Wang, Quan Gan, David Wipf, Zheng Zhang, Christos Faloutsos, Weinan Zhang, Muhan Zhang, Zhenkun Cai, Jiahang Li, Zunyao Mao, Yakun Song, Jianheng Tang, Yanlin Zhang, Guang Yang, Chuan Lei, Xiao Qin, Ning Li, Han Zhang, Yanbo Wang, Zizhao Zhang
2024	—	`conf`	4DBInfer: A 4D Benchmarking Toolbox for Graph-Centric Predictive Modeling on RDBs. VLDB Workshops Minjie Wang, Quan Gan, David Wipf, Zhenkun Cai, Ning Li, Jianheng Tang, Yanlin Zhang, Zizhao Zhang, Zunyao Mao, Yakun Song, Yanbo Wang, Jiahang Li, Han Zhang, Guang Yang, Xiao Qin, Chuan Lei, Muhan Zhang, Weinan Zhang, Christos Faloutsos, Zheng Zhang
2024	J	`jnl`	4DBInfer: A 4D Benchmarking Toolbox for Graph-Centric Predictive Modeling on Relational DBs. CoRR Minjie Wang, Quan Gan, David Wipf, Zhenkun Cai, Ning Li, Jianheng Tang, Yanlin Zhang, Zizhao Zhang, Zunyao Mao, Yakun Song, Yanbo Wang, Jiahang Li, Han Zhang, Guang Yang, Xiao Qin, Chuan Lei, Muhan Zhang, Weinan Zhang, Christos Faloutsos, Zheng Zhang
2024	J	`jnl`	BloomGML: Graph Machine Learning through the Lens of Bilevel Optimization. CoRR Amber Yijia Zheng, Tong He, Yixuan Qiu, Minjie Wang, David Wipf
2024	A	`conf`	ELF-Gym: Evaluating Large Language Models Generated Features for Tabular Prediction. CIKM Yanlin Zhang, Ning Li, Quan Gan, Weinan Zhang, David Wipf, Minjie Wang
2024	J	`jnl`	ELF-Gym: Evaluating Large Language Models Generated Features for Tabular Prediction. CoRR Yanlin Zhang, Ning Li, Quan Gan, Weinan Zhang, David Wipf, Minjie Wang
2024	J	`jnl`	FreshGNN: Reducing Memory Access via Stable Historical Embeddings for Graph Neural Network Training. Proc. VLDB Endow. Kezhao Huang, Haitian Jiang, Minjie Wang, Guangxuan Xiao, David Wipf, Xiang Song, Quan Gan, Zengfeng Huang, Jidong Zhai, Zheng Zhang
2024	—	`conf`	GFS: Graph-based Feature Synthesis for Prediction over Relational Databases. VLDB Workshops Han Zhang, Quan Gan, David Wipf, Weinan Zhang
2024	A*	`conf`	Graph Machine Learning Meets Multi-Table Relational Data. KDD Quan Gan, Minjie Wang, David Wipf, Christos Faloutsos
2024	A	`conf`	Graph Machine Learning through the Lens of Bilevel Optimization. AISTATS Amber Yijia Zheng, Tong He, Yixuan Qiu, Minjie Wang, David Wipf
2024	J	`jnl`	Graph Neural Networks Formed via Layer-wise Ensembles of Heterogeneous Base Models. Trans. Mach. Learn. Res. Jiuhai Chen, Jonas Mueller, Vassilis N. Ioannidis, Tom Goldstein, David Wipf
2024	A*	`conf`	How Graph Neural Networks Learn: Lessons from Training Dynamics. ICML Chenxiao Yang, Qitian Wu, David Wipf, Ruoyu Sun, Junchi Yan
2024	J	`jnl`	Neural Message Passing Induced by Energy-Constrained Diffusion. CoRR Qitian Wu, David Wipf, Junchi Yan
2024	J	`jnl`	New Desiderata for Direct Preference Optimization. CoRR Xiangkun Hu, Tong He, David Wipf
2024	A*	`conf`	Robust Angular Synchronization via Directed Graph Neural Networks. ICLR Yixuan He, Gesine Reinert, David Wipf, Mihai Cucuringu
2024	J	`jnl`	SGFormer: Single-Layer Graph Transformers with Approximation-Free Linear Complexity. CoRR Qitian Wu, Kai Yang, Hengrui Zhang, David Wipf, 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	J	`jnl`	Efficient Link Prediction via GNN Layers Induced by Negative Sampling. CoRR Yuxin Wang, Xiannian Hu, Quan Gan, Xuanjing Huang, Xipeng Qiu, David Wipf
2023	A*	`conf`	From Hypergraph Energy Functions to Hypergraph Neural Networks. ICML Yuxin Wang, Quan Gan, Xipeng Qiu, Xuanjing Huang, David Wipf
2023	J	`jnl`	From Hypergraph Energy Functions to Hypergraph Neural Networks. CoRR Yuxin Wang, Quan Gan, Xipeng Qiu, Xuanjing Huang, David Wipf
2023	J	`jnl`	GFS: Graph-based Feature Synthesis for Prediction over Relational Databases. CoRR Han Zhang, Quan Gan, David Wipf, Weinan Zhang
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 Manifold Dimensions with Conditional Variational Autoencoders. CoRR Yijia Zheng, Tong He, Yixuan Qiu, David Wipf
2023	A*	`conf`	Marginalization is not Marginal: No Bad VAE Local Minima when Learning Optimal Sparse Representations. ICML David Wipf
2023	J	`jnl`	MuseGNN: Interpretable and Convergent Graph Neural Network Layers at Scale. CoRR Haitian Jiang, Renjie Liu, Xiao Yan, Zhenkun Cai, Minjie Wang, David Wipf
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	A*	`conf`	On the Initialization of Graph Neural Networks. ICML Jiahang Li, Yakun Song, Xiang Song, David Wipf
2023	J	`jnl`	ReFresh: Reducing Memory Access from Exploiting Stable Historical Embeddings for Graph Neural Network Training. CoRR Kezhao Huang, Haitian Jiang, Minjie Wang, Guangxuan Xiao, David Wipf, Xiang Song, Quan Gan, Zengfeng Huang, Jidong Zhai, Zheng Zhang
2023	J	`jnl`	Robust Angular Synchronization via Directed Graph Neural Networks. CoRR Yixuan He, Gesine Reinert, David Wipf, Mihai Cucuringu
2022	J	`jnl`	A Robust Stacking Framework for Training Deep Graph Models with Multifaceted Node Features. CoRR Jiuhai Chen, Jonas Mueller, Vassilis N. Ioannidis, Tom Goldstein, David Wipf
2022	J	`jnl`	Descent Steps of a Relation-Aware Energy Produce Heterogeneous Graph Neural Networks. CoRR Hongjoon Ahn, Yongyi Yang, Quan Gan, David Wipf, Taesup Moon
2022	A*	`conf`	Does your graph need a confidence boost? Convergent boosted smoothing on graphs with tabular node features. ICLR Jiuhai Chen, Jonas Mueller, Vassilis N. Ioannidis, Soji Adeshina, Yangkun Wang, Tom Goldstein, David Wipf
2022	J	`jnl`	Face Restoration via Plug-and-Play 3D Facial Priors. IEEE Trans. Pattern Anal. Mach. Intell. Xiaobin Hu, Wenqi Ren, Jiaolong Yang, Xiaochun Cao, David Wipf, Bjoern H. Menze, Xin Tong, Hongbin Zha
2022	A*	`conf`	GNNRank: Learning Global Rankings from Pairwise Comparisons via Directed Graph Neural Networks. ICML Yixuan He, Quan Gan, David Wipf, Gesine D. Reinert, Junchi Yan, Mihai Cucuringu
2022	J	`jnl`	GNNRank: Learning Global Rankings from Pairwise Comparisons via Directed Graph Neural Networks. CoRR Yixuan He, Quan Gan, David Wipf, Gesine Reinert, Junchi Yan, Mihai Cucuringu
2022	A*	`conf`	Handling Distribution Shifts on Graphs: An Invariance Perspective. ICLR Qitian Wu, Hengrui Zhang, Junchi Yan, David Wipf
2022	A*	`conf`	Inductive Relation Prediction Using Analogy Subgraph Embeddings. ICLR Jiarui Jin, Yangkun Wang, Kounianhua Du, Weinan Zhang, Zheng Zhang, David Wipf, Yong Yu, Quan Gan
2022	J	`jnl`	Learning Enhanced Representations for Tabular Data via Neighborhood Propagation. CoRR Kounianhua Du, Weinan Zhang, Ruiwen Zhou, Yangkun Wang, Xilong Zhao, Jiarui Jin, Quan Gan, Zheng Zhang, David Wipf
2022	J	`jnl`	Self-supervised Amodal Video Object Segmentation. CoRR Jian Yao, Yuxin Hong, Chiyu Wang, Tianjun Xiao, Tong He, Francesco Locatello, David Wipf, Yanwei Fu, Zheng Zhang
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	J	`jnl`	Transformers from an Optimization Perspective. CoRR Yongyi Yang, Zengfeng Huang, David Wipf
2022	A*	`conf`	Why Propagate Alone? Parallel Use of Labels and Features on Graphs. ICLR Yangkun Wang, Jiarui Jin, Weinan Zhang, Yongyi Yang, Jiuhai Chen, Quan Gan, Yong Yu, Zheng Zhang, Zengfeng Huang, David Wipf
2021	A*	`conf`	A Biased Graph Neural Network Sampler with Near-Optimal Regret. NeurIPS Qingru Zhang, David Wipf, Quan Gan, Le Song
2021	J	`jnl`	A Biased Graph Neural Network Sampler with Near-Optimal Regret. CoRR Qingru Zhang, David Wipf, Quan Gan, Le Song
2021	J	`jnl`	Convergent Boosted Smoothing for Modeling Graph Data with Tabular Node Features. CoRR Jiuhai Chen, Jonas Mueller, Vassilis N. Ioannidis, Soji Adeshina, Yangkun Wang, Tom Goldstein, David Wipf
2021	Misc	`conf`	Deep Learning for Linear Inverse Problems Using the Plug-and-Play Priors Framework. ICASSP Wei Chen, David Wipf, Miguel Rodrigues
2021	A	`conf`	Fork or Fail: Cycle-Consistent Training with Many-to-One Mappings. AISTATS Qipeng Guo, Zhijing Jin, Ziyu Wang, Xipeng Qiu, Weinan Zhang, Jun Zhu, Zheng Zhang, David Wipf
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`	GRIN: Generative Relation and Intention Network for Multi-agent Trajectory Prediction. NeurIPS Longyuan Li, Jian Yao, Li K. Wenliang, Tong He, Tianjun Xiao, Junchi Yan, David Wipf, Zheng Zhang
2021	A*	`conf`	Graph Neural Networks Inspired by Classical Iterative Algorithms. ICML Yongyi Yang, Tang Liu, Yangkun Wang, Jinjing Zhou, Quan Gan, Zhewei Wei, Zheng Zhang, Zengfeng Huang, David Wipf
2021	J	`jnl`	Graph Neural Networks Inspired by Classical Iterative Algorithms. CoRR Yongyi Yang, Tang Liu, Yangkun Wang, Jinjing Zhou, Quan Gan, Zhewei Wei, Zheng Zhang, Zengfeng Huang, David Wipf
2021	J	`jnl`	Implicit vs Unfolded Graph Neural Networks. CoRR Yongyi Yang, Yangkun Wang, Zengfeng Huang, David Wipf
2021	A*	`conf`	Learning Hierarchical Graph Neural Networks for Image Clustering. ICCV Yifan Xing, Tong He, Tianjun Xiao, Yongxin Wang, Yuanjun Xiong, Wei Xia, David Wipf, Zheng Zhang, Stefano Soatto
2021	J	`jnl`	Learning Hierarchical Graph Neural Networks for Image Clustering. CoRR Yifan Xing, Tong He, Tianjun Xiao, Yongxin Wang, Yuanjun Xiong, Wei Xia, David Wipf, Zheng Zhang, Stefano Soatto
2021	A*	`conf`	Sparse Multi-Path Corrections in Fringe Projection Profilometry. CVPR Yu Zhang, Daniel L. Lau, David Wipf
2021	J	`jnl`	Why Propagate Alone? Parallel Use of Labels and Features on Graphs. CoRR Yangkun Wang, Jiarui Jin, Weinan Zhang, Yongyi Yang, Jiuhai Chen, Quan Gan, Yong Yu, Zheng Zhang, Zengfeng Huang, David Wipf
2020	J	`jnl`	CycleGT: Unsupervised Graph-to-Text and Text-to-Graph Generation via Cycle Training. CoRR Qipeng Guo, Zhijing Jin, Xipeng Qiu, Weinan Zhang, David Wipf, Zheng Zhang
2020	J	`jnl`	Fork or Fail: Cycle-Consistent Training with Many-to-One Mappings. CoRR Qipeng Guo, Zhijing Jin, Ziyu Wang, Xipeng Qiu, Weinan Zhang, Jun Zhu, Zheng Zhang, David Wipf
2020	—	`conf`	Further Analysis of Outlier Detection with Deep Generative Models. ICBINB@NeurIPS Ziyu Wang, Bin Dai, David Wipf, Jun Zhu