2026 David Wipf: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	40	9126	8864	3880	3722	123	9672

Overview

David Wipf is a researcher affiliated with Amazon in the United States. Their main field of study is Computer Science, with a primary focus on subfields such as Artificial Intelligence, Computer Vision and Pattern Recognition, Statistical and Nonlinear Physics, Cognitive Neuroscience, and Electrical and Electronic Engineering.

The research topics covered by David Wipf include:

Advanced Graph Neural Networks
Graph Theory and Algorithms
Topic Modeling
Complex Network Analysis Techniques
Generative Adversarial Networks and Image Synthesis
Bioinformatics and Genomic Networks
Advanced Image and Video Retrieval Techniques

David Wipf has contributed extensively to academic publications, with frequent papers appearing in several venues. Their most common publication outlets are:

arXiv (Cornell University)
IEEE Transactions on Pattern Analysis and Machine Intelligence
2021 IEEE/CVF International Conference on Computer Vision (ICCV)
IEEE Transactions on Knowledge and Data Engineering
Proceedings of the VLDB Endowment

Recent papers authored by or involving David Wipf include:

From Canonical Correlation Analysis to Self-supervised Graph Neural Networks, 2021, arXiv (Cornell University)
NodeFormer: A Scalable Graph Structure Learning Transformer for Node Classification, 2023, arXiv (Cornell University)
Sparse Bayesian Learning for End-to-End EEG Decoding, 2023, IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning Hierarchical Graph Neural Networks for Image Clustering, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

The researcher collaborates regularly with several coauthors, notable among them are:

Zheng Zhang (12 joint publications)
Junchi Yan (8 joint publications)
Weinan Zhang (8 joint publications)
Quan Gan (8 joint publications)
Qitian Wu (7 joint publications)

Best Publications

Sparse Bayesian learning for basis selection

D.P. Wipf;B.D. Rao

1712
Citations
An Empirical Bayesian Strategy for Solving the Simultaneous Sparse Approximation Problem

D.P. Wipf;B.D. Rao

1008
Citations
Iterative Reweighted $ll_1$ and $ll_2$ Methods for Finding Sparse Solutions

D. Wipf;S. Nagarajan

537
Citations
A unified Bayesian framework for MEG/EEG source imaging.

David P. Wipf;Srikantan S. Nagarajan

426
Citations
A New View of Automatic Relevance Determination

David P. Wipf;Srikantan S. Nagarajan

384
Citations
Lane Change Intent Analysis Using Robust Operators and Sparse Bayesian Learning

J.C. McCall;D.P. Wipf;M.M. Trivedi;B.D. Rao

381
Citations
Latent Variable Bayesian Models for Promoting Sparsity

D. P. Wipf;B. D. Rao;S. Nagarajan

361
Citations
A Generic Deep Architecture for Single Image Reflection Removal and Image Smoothing

Qingnan Fan;Jiaolong Yang;Gang Hua;Baoquan Chen

322
Citations
Robust Bayesian estimation of the location, orientation, and time course of multiple correlated neural sources using MEG.

David P. Wipf;Julia P. Owen;Hagai Thomas Attias;Kensuke Sekihara

260
Citations
A Practical Transfer Learning Algorithm for Face Verification

Xudong Cao;David Wipf;Fang Wen;Genquan Duan

252
Citations
Diagnosing and Enhancing VAE Models

Bin Dai;David P. Wipf

243
Citations
Unsupervised Extraction of Video Highlights via Robust Recurrent Auto-Encoders

Huan Yang;Baoyuan Wang;Stephen Lin;David Wipf

224
Citations
Variational EM Algorithms for Non-Gaussian Latent Variable Models

Jason Palmer;Kenneth Kreutz-Delgado;Bhaskar D. Rao;David P. Wipf

217
Citations
Multi-image Blind Deblurring Using a Coupled Adaptive Sparse Prior

Haichao Zhang;David Wipf;Yanning Zhang

193
Citations
Robust photometric stereo using sparse regression

Satoshi Ikehata;David Wipf;Yasuyuki Matsushita;Kiyoharu Aizawa

183
Citations
Perspectives on Sparse Bayesian Learning

Jason Palmer;Bhaskar D. Rao;David P. Wipf

146
Citations
Single Image Reflection Removal Exploiting Misaligned Training Data and Network Enhancements

Kaixuan Wei;Jiaolong Yang;Ying Fu;David Wipf

145
Citations
Maximal Sparsity with Deep Networks

Bo Xin;Yizhou Wang;Wen Gao;David P. Wipf

128
Citations
Image smoothing via unsupervised learning

Qingnan Fan;Jiaolong Yang;David Wipf;Baoquan Chen

128
Citations
Revisiting Deep Intrinsic Image Decompositions

Qingnan Fan;Jiaolong Yang;Gang Hua;Baoquan Chen

120
Citations
Lane Change Intent Analysis Using Robust Operators and Sparse Bayesian Learning

J.C. McCall;M.M. Trivedi;D. Wipf;Bhaskar Rao

90
Citations
Compressing Neural Networks using the Variational Information Bottleneck

Bin Dai;Chen Zhu;David Wipf

46
Citations

Frequent Co-Authors

Srikantan S. Nagarajan University of California, San Francisco

Bhaskar D. Rao University of California, San Diego

Gang Hua Dolby (United States)

Baoquan Chen Peking University

Yizhou Wang Peking University

Lars Kai Hansen Technical University of Denmark

Yasuyuki Matsushita Microsoft Research Asia Tokyo

Xin Tong Microsoft Research Asia (China)

Kenneth Kreutz-Delgado University of California, San Diego

In So Kweon Korea Advanced Institute of Science and Technology

External Links

Personal website of David Wipf

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