David Wipf

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 54

Top Topics

Predictive Model

Relational Data

Top Venues

Publications

Xiangkun Hu, Tong He, David Wipf
New Desiderata for Direct Preference Optimization. CoRR (2024)
Kezhao Huang, Haitian Jiang, Minjie Wang, Guangxuan Xiao, David Wipf, Xiang Song, Quan Gan, Zengfeng Huang, Jidong Zhai, Zheng Zhang
FreshGNN: Reducing Memory Access via Stable Historical Embeddings for Graph Neural Network Training. Proc. VLDB Endow. 17 (6) (2024)
Amber Yijia Zheng, Tong He, Yixuan Qiu, Minjie Wang, David Wipf
BloomGML: Graph Machine Learning through the Lens of Bilevel Optimization. CoRR (2024)
Quan Gan, Minjie Wang, David Wipf, Christos Faloutsos
Graph Machine Learning Meets Multi-Table Relational Data. KDD (2024)
Amber Yijia Zheng, Tong He, Yixuan Qiu, Minjie Wang, David Wipf
Graph Machine Learning through the Lens of Bilevel Optimization. AISTATS (2024)
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
4DBInfer: A 4D Benchmarking Toolbox for Graph-Centric Predictive Modeling on Relational DBs. CoRR (2024)
Yixuan He, Gesine Reinert, David Wipf, Mihai Cucuringu
Robust Angular Synchronization via Directed Graph Neural Networks. ICLR (2024)
Jiuhai Chen, Jonas Mueller, Vassilis N. Ioannidis, Tom Goldstein, David Wipf
Graph Neural Networks Formed via Layer-wise Ensembles of Heterogeneous Base Models. Trans. Mach. Learn. Res. 2024 (2024)
Qitian Wu, Chenxiao Yang, Wentao Zhao, Yixuan He, David Wipf, Junchi Yan
DIFFormer: Scalable (Graph) Transformers Induced by Energy Constrained Diffusion. ICLR (2023)
Yixuan He, Gesine Reinert, David Wipf, Mihai Cucuringu
Robust Angular Synchronization via Directed Graph Neural Networks. CoRR (2023)
Yuxin Wang, Quan Gan, Xipeng Qiu, Xuanjing Huang, David Wipf
From Hypergraph Energy Functions to Hypergraph Neural Networks. CoRR (2023)
Haitian Jiang, Renjie Liu, Xiao Yan, Zhenkun Cai, Minjie Wang, David Wipf
MuseGNN: Interpretable and Convergent Graph Neural Network Layers at Scale. CoRR (2023)
Yijia Zheng, Tong He, Yixuan Qiu, David Wipf
Learning Manifold Dimensions with Conditional Variational Autoencoders. CoRR (2023)
Han Zhang, Quan Gan, David Wipf, Weinan Zhang
GFS: Graph-based Feature Synthesis for Prediction over Relational Databases. CoRR (2023)
Qitian Wu, Chenxiao Yang, Wentao Zhao, Yixuan He, David Wipf, Junchi Yan
DIFFormer: Scalable (Graph) Transformers Induced by Energy Constrained Diffusion. CoRR (2023)
Yuxin Wang, Quan Gan, Xipeng Qiu, Xuanjing Huang, David Wipf
From Hypergraph Energy Functions to Hypergraph Neural Networks. ICML (2023)
Chenxiao Yang, Qitian Wu, David Wipf, Ruoyu Sun, Junchi Yan
How Graph Neural Networks Learn: Lessons from Training Dynamics in Function Space. CoRR (2023)
Jiahang Li, Yakun Song, Xiang Song, David Wipf
On the Initialization of Graph Neural Networks. ICML (2023)
Qitian Wu, Wentao Zhao, Zenan Li, David Wipf, Junchi Yan
NodeFormer: A Scalable Graph Structure Learning Transformer for Node Classification. CoRR (2023)
David Wipf
Marginalization is not Marginal: No Bad VAE Local Minima when Learning Optimal Sparse Representations. ICML (2023)
Kezhao Huang, Haitian Jiang, Minjie Wang, Guangxuan Xiao, David Wipf, Xiang Song, Quan Gan, Zengfeng Huang, Jidong Zhai, Zheng Zhang
ReFresh: Reducing Memory Access from Exploiting Stable Historical Embeddings for Graph Neural Network Training. CoRR (2023)
Yuxin Wang, Xiannian Hu, Quan Gan, Xuanjing Huang, Xipeng Qiu, David Wipf
Efficient Link Prediction via GNN Layers Induced by Negative Sampling. CoRR (2023)
Jiarui Jin, Yangkun Wang, Weinan Zhang, Quan Gan, Xiang Song, Yong Yu, Zheng Zhang, David Wipf
Refined Edge Usage of Graph Neural Networks for Edge Prediction. CoRR (2022)
Yangkun Wang, Jiarui Jin, Weinan Zhang, Yongyi Yang, Jiuhai Chen, Quan Gan, Yong Yu, Zheng Zhang, Zengfeng Huang, David Wipf
Why Propagate Alone? Parallel Use of Labels and Features on Graphs. ICLR (2022)
Jiarui Jin, Yangkun Wang, Kounianhua Du, Weinan Zhang, Zheng Zhang, David Wipf, Yong Yu, Quan Gan
Inductive Relation Prediction Using Analogy Subgraph Embeddings. ICLR (2022)
Xiaobin Hu, Wenqi Ren, Jiaolong Yang, Xiaochun Cao, David Wipf, Bjoern H. Menze, Xin Tong, Hongbin Zha
Face Restoration via Plug-and-Play 3D Facial Priors. IEEE Trans. Pattern Anal. Mach. Intell. 44 (12) (2022)
Jiuhai Chen, Jonas Mueller, Vassilis N. Ioannidis, Soji Adeshina, Yangkun Wang, Tom Goldstein, David Wipf
Does your graph need a confidence boost? Convergent boosted smoothing on graphs with tabular node features. ICLR (2022)
Yongyi Yang, Zengfeng Huang, David Wipf
Transformers from an Optimization Perspective. CoRR (2022)
Kounianhua Du, Weinan Zhang, Ruiwen Zhou, Yangkun Wang, Xilong Zhao, Jiarui Jin, Quan Gan, Zheng Zhang, David Wipf
Learning Enhanced Representations for Tabular Data via Neighborhood Propagation. CoRR (2022)
Jiuhai Chen, Jonas Mueller, Vassilis N. Ioannidis, Tom Goldstein, David Wipf
A Robust Stacking Framework for Training Deep Graph Models with Multifaceted Node Features. CoRR (2022)
Hongjoon Ahn, Yongyi Yang, Quan Gan, David Wipf, Taesup Moon
Descent Steps of a Relation-Aware Energy Produce Heterogeneous Graph Neural Networks. CoRR (2022)
Yixuan He, Quan Gan, David Wipf, Gesine Reinert, Junchi Yan, Mihai Cucuringu
GNNRank: Learning Global Rankings from Pairwise Comparisons via Directed Graph Neural Networks. CoRR (2022)
Qitian Wu, Hengrui Zhang, Junchi Yan, David Wipf
Towards Distribution Shift of Node-Level Prediction on Graphs: An Invariance Perspective. CoRR (2022)
Qitian Wu, Hengrui Zhang, Junchi Yan, David Wipf
Handling Distribution Shifts on Graphs: An Invariance Perspective. ICLR (2022)
Yixuan He, Quan Gan, David Wipf, Gesine D. Reinert, Junchi Yan, Mihai Cucuringu
GNNRank: Learning Global Rankings from Pairwise Comparisons via Directed Graph Neural Networks. ICML (2022)
Jian Yao, Yuxin Hong, Chiyu Wang, Tianjun Xiao, Tong He, Francesco Locatello, David Wipf, Yanwei Fu, Zheng Zhang
Self-supervised Amodal Video Object Segmentation. CoRR (2022)
Wei Chen, David Wipf, Miguel Rodrigues
Deep Learning for Linear Inverse Problems Using the Plug-and-Play Priors Framework. ICASSP (2021)
Qingru Zhang, David Wipf, Quan Gan, Le Song
A Biased Graph Neural Network Sampler with Near-Optimal Regret. NeurIPS (2021)
Hengrui Zhang, Qitian Wu, Junchi Yan, David Wipf, Philip S. Yu
From Canonical Correlation Analysis to Self-supervised Graph Neural Networks. NeurIPS (2021)
Qingru Zhang, David Wipf, Quan Gan, Le Song
A Biased Graph Neural Network Sampler with Near-Optimal Regret. CoRR (2021)
Yifan Xing, Tong He, Tianjun Xiao, Yongxin Wang, Yuanjun Xiong, Wei Xia, David Wipf, Zheng Zhang, Stefano Soatto
Learning Hierarchical Graph Neural Networks for Image Clustering. CoRR (2021)
Yangkun Wang, Jiarui Jin, Weinan Zhang, Yongyi Yang, Jiuhai Chen, Quan Gan, Yong Yu, Zheng Zhang, Zengfeng Huang, David Wipf
Why Propagate Alone? Parallel Use of Labels and Features on Graphs. CoRR (2021)
Yu Zhang, Daniel L. Lau, David Wipf
Sparse Multi-Path Corrections in Fringe Projection Profilometry. CVPR (2021)
Yongyi Yang, Tang Liu, Yangkun Wang, Jinjing Zhou, Quan Gan, Zhewei Wei, Zheng Zhang, Zengfeng Huang, David Wipf
Graph Neural Networks Inspired by Classical Iterative Algorithms. ICML (2021)
Yongyi Yang, Yangkun Wang, Zengfeng Huang, David Wipf
Implicit vs Unfolded Graph Neural Networks. CoRR (2021)
Hengrui Zhang, Qitian Wu, Junchi Yan, David Wipf, Philip S. Yu
From Canonical Correlation Analysis to Self-supervised Graph Neural Networks. CoRR (2021)
Yongyi Yang, Tang Liu, Yangkun Wang, Jinjing Zhou, Quan Gan, Zhewei Wei, Zheng Zhang, Zengfeng Huang, David Wipf
Graph Neural Networks Inspired by Classical Iterative Algorithms. CoRR (2021)
Qipeng Guo, Zhijing Jin, Ziyu Wang, Xipeng Qiu, Weinan Zhang, Jun Zhu, Zheng Zhang, David Wipf
Fork or Fail: Cycle-Consistent Training with Many-to-One Mappings. AISTATS (2021)
Jiuhai Chen, Jonas Mueller, Vassilis N. Ioannidis, Soji Adeshina, Yangkun Wang, Tom Goldstein, David Wipf
Convergent Boosted Smoothing for Modeling Graph Data with Tabular Node Features. CoRR (2021)
Longyuan Li, Jian Yao, Li Wenliang, Tong He, Tianjun Xiao, Junchi Yan, David Wipf, Zheng Zhang
GRIN: Generative Relation and Intention Network for Multi-agent Trajectory Prediction. NeurIPS (2021)
Yifan Xing, Tong He, Tianjun Xiao, Yongxin Wang, Yuanjun Xiong, Wei Xia, David Wipf, Zheng Zhang, Stefano Soatto
Learning Hierarchical Graph Neural Networks for Image Clustering. ICCV (2021)
Qipeng Guo, Zhijing Jin, Ziyu Wang, Xipeng Qiu, Weinan Zhang, Jun Zhu, Zheng Zhang, David Wipf
Fork or Fail: Cycle-Consistent Training with Many-to-One Mappings. CoRR (2020)
Qipeng Guo, Zhijing Jin, Xipeng Qiu, Weinan Zhang, David Wipf, Zheng Zhang
CycleGT: Unsupervised Graph-to-Text and Text-to-Graph Generation via Cycle Training. CoRR (2020)
Ziyu Wang, Bin Dai, David Wipf, Jun Zhu
Further Analysis of Outlier Detection with Deep Generative Models. ICBINB@NeurIPS (2020)