David Wipf

Engineering · Physical Sciences

38h-index8.4kcitations167works2.22yr avg
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Research Topics

Sparse and Compressive Sensing Techniques(45), Blind Source Separation Techniques(32), Advanced Graph Neural Networks(31), Advanced Image Processing Techniques(17), Generative Adversarial Networks and Image Synthesis(13)

Publications167 total

TaTToo: Tool-Grounded Thinking PRM for Test-Time Scaling in Tabular Reasoning
arXiv (Cornell University)·2025Open Access
Sparse Autoencoders, Again?
arXiv (Cornell University)·2025Open Access
Griffin: Towards a Graph-Centric Relational Database Foundation Model
arXiv (Cornell University)·2025Open Access
Prior-Fitted Networks Scale to Larger Datasets When Treated as Weak Learners
arXiv (Cornell University)·2025Open Access
Learning to Fuse Temporal Proximity Networks: A Case Study in Chimpanzee Social Interactions
arXiv (Cornell University)·2025Open Access
ELF-Gym: Evaluating Large Language Models Generated Features for Tabular Prediction
2024· 1 cited
Efficient Link Prediction via GNN Layers Induced by Negative Sampling
IEEE Transactions on Knowledge and Data Engineering·2024· 11 cited
ELF-Gym: Evaluating Large Language Models Generated Features for Tabular Prediction
arXiv (Cornell University)·2024Open Access
SGFormer: Single-Layer Graph Transformers with Approximation-Free Linear Complexity
arXiv (Cornell University)·2024· 1 citedOpen Access
Graph Machine Learning Meets Multi-Table Relational Data
2024· 3 citedOpen Access
4DBInfer: A 4D Benchmarking Toolbox for Graph-Centric Predictive Modeling on Relational DBs
arXiv (Cornell University)·2024Open Access
BloomGML: Graph Machine Learning through the Lens of Bilevel Optimization
arXiv (Cornell University)·2024· 2 citedOpen Access
FreshGNN: Reducing Memory Access via Stable Historical Embeddings for Graph Neural Network Training
Proceedings of the VLDB Endowment·2024· 11 cited
4DBInfer: A 4D Benchmarking Toolbox for Graph-Centric Predictive Modeling on RDBs
2024· 2 cited
On the Initialization of Graph Neural Networks
arXiv (Cornell University)·2023· 1 citedOpen Access
GFS: Graph-based Feature Synthesis for Prediction over Relational Databases
arXiv (Cornell University)·2023Open Access
MuseGNN: Forming Scalable, Convergent GNN Layers that Minimize a Sampling-Based Energy
arXiv (Cornell University)·2023Open Access
Efficient Link Prediction via GNN Layers Induced by Negative Sampling
arXiv (Cornell University)·2023Open Access
Robust Angular Synchronization via Directed Graph Neural Networks
arXiv (Cornell University)·2023Open Access
How Graph Neural Networks Learn: Lessons from Training Dynamics
arXiv (Cornell University)·2023Open Access
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Frequent Co-authors

Bhaskar D. Rao(9), Srikantan S. Nagarajan(6), Jiaolong Yang(5), Haichao Zhang(5), Xin Tong(4), Qitian Wu(4), Junchi Yan(4), Bin Dai(4), Qingnan Fan(3), Gang Hua(3), Baoquan Chen(3), Jason Palmer(3), Hengrui Zhang(3), J.C. McCall(2), Mohan M. Trivedi(2), Julia P. Owen(2), Hagai Attias(2), Kensuke Sekihara(2), Yanning Zhang(2), Baoyuan Wang(2)