David Wipf
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
28
Venues
9
Active years
2021–2025
Best venue rank
A*
Where they publish
Papers
28 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | AISTATS | Common Learning Constraints Alter Interpretations of Direct Preference Optimization. | Lemin Kong, Xiangkun Hu, Tong He, David Wipf |
| 2025 | AISTATS | Prior-Fitted Networks Scale to Larger Datasets When Treated as Weak Learners. | Yuxin Wang, Botian Jiang, Yiran Guo, Quan Gan, David Wipf, Xuanjing Huang, Xipeng Qiu |
| 2025 | ICLR | MuseGNN: Forming Scalable, Convergent GNN Layers that Minimize a Sampling-Based Energy. | Haitian Jiang, Renjie Liu, Zengfeng Huang, Yichuan Wang, Xiao Yan, Zhenkun Cai, Minjie Wang, David Wipf |
| 2025 | ICLR | Chain-of-Thought Provably Enables Learning the (Otherwise) Unlearnable. | Chenxiao Yang, Zhiyuan Li, David Wipf |
| 2025 | ICML | Explicit Preference Optimization: No Need for an Implicit Reward Model. | Xiangkun Hu, Lemin Kong, Tong He, David Wipf |
| 2025 | ICML | Sparse Autoencoders, Again? | Yin Lu, Xuening Zhu, Tong He, David Wipf |
| 2025 | ICML | Griffin: Towards a Graph-Centric Relational Database Foundation Model. | Yanbo Wang, Xiyuan Wang, Quan Gan, Minjie Wang, Qibin Yang, David Wipf, Muhan Zhang |
| 2024 | AISTATS | Graph Machine Learning through the Lens of Bilevel Optimization. | Amber Yijia Zheng, Tong He, Yixuan Qiu, Minjie Wang, David Wipf |
| 2024 | CIKM | ELF-Gym: Evaluating Large Language Models Generated Features for Tabular Prediction. | Yanlin Zhang, Ning Li, Quan Gan, Weinan Zhang, David Wipf, Minjie Wang |
| 2024 | ICLR | Robust Angular Synchronization via Directed Graph Neural Networks. | Yixuan He, Gesine Reinert, David Wipf, Mihai Cucuringu |
| 2024 | ICML | How Graph Neural Networks Learn: Lessons from Training Dynamics. | Chenxiao Yang, Qitian Wu, David Wipf, Ruoyu Sun, Junchi Yan |
| 2024 | KDD | Graph Machine Learning Meets Multi-Table Relational Data. | Quan Gan, Minjie Wang, David Wipf, Christos Faloutsos |
| 2024 | VLDB | GFS: Graph-based Feature Synthesis for Prediction over Relational Databases. | Han Zhang, Quan Gan, David Wipf, Weinan Zhang |
| 2024 | VLDB | 4DBInfer: A 4D Benchmarking Toolbox for Graph-Centric Predictive Modeling on RDBs. | 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 |
| 2023 | ICLR | DIFFormer: Scalable (Graph) Transformers Induced by Energy Constrained Diffusion. | Qitian Wu, Chenxiao Yang, Wentao Zhao, Yixuan He, David Wipf, Junchi Yan |
| 2023 | ICML | On the Initialization of Graph Neural Networks. | Jiahang Li, Yakun Song, Xiang Song, David Wipf |
| 2023 | ICML | From Hypergraph Energy Functions to Hypergraph Neural Networks. | Yuxin Wang, Quan Gan, Xipeng Qiu, Xuanjing Huang, David Wipf |
| 2023 | ICML | Marginalization is not Marginal: No Bad VAE Local Minima when Learning Optimal Sparse Representations. | David Wipf |
| 2022 | ICLR | Does your graph need a confidence boost? Convergent boosted smoothing on graphs with tabular node features. | Jiuhai Chen, Jonas Mueller, Vassilis N. Ioannidis, Soji Adeshina, Yangkun Wang, Tom Goldstein, David Wipf |
| 2022 | ICLR | Inductive Relation Prediction Using Analogy Subgraph Embeddings. | Jiarui Jin, Yangkun Wang, Kounianhua Du, Weinan Zhang, Zheng Zhang, David Wipf, Yong Yu, Quan Gan |
| 2022 | ICLR | Why Propagate Alone? Parallel Use of Labels and Features on Graphs. | Yangkun Wang, Jiarui Jin, Weinan Zhang, Yongyi Yang, Jiuhai Chen, Quan Gan, Yong Yu, Zheng Zhang, Zengfeng Huang, David Wipf |
| 2022 | ICLR | Handling Distribution Shifts on Graphs: An Invariance Perspective. | Qitian Wu, Hengrui Zhang, Junchi Yan, David Wipf |
| 2022 | ICML | GNNRank: Learning Global Rankings from Pairwise Comparisons via Directed Graph Neural Networks. | Yixuan He, Quan Gan, David Wipf, Gesine D. Reinert, Junchi Yan, Mihai Cucuringu |
| 2021 | AISTATS | Fork or Fail: Cycle-Consistent Training with Many-to-One Mappings. | Qipeng Guo, Zhijing Jin, Ziyu Wang, Xipeng Qiu, Weinan Zhang, Jun Zhu, Zheng Zhang, David Wipf |
| 2021 | CVPR | Sparse Multi-Path Corrections in Fringe Projection Profilometry. | Yu Zhang, Daniel L. Lau, David Wipf |
| 2021 | ICASSP | Deep Learning for Linear Inverse Problems Using the Plug-and-Play Priors Framework. | Wei Chen, David Wipf, Miguel Rodrigues |
| 2021 | ICCV | Learning Hierarchical Graph Neural Networks for Image Clustering. | Yifan Xing, Tong He, Tianjun Xiao, Yongxin Wang, Yuanjun Xiong, Wei Xia, David Wipf, Zheng Zhang, Stefano Soatto |
| 2021 | ICML | Graph Neural Networks Inspired by Classical Iterative Algorithms. | Yongyi Yang, Tang Liu, Yangkun Wang, Jinjing Zhou, Quan Gan, Zhewei Wei, Zheng Zhang, Zengfeng Huang, David Wipf |