David Wipf © All rights reserved.

For older publications please see my previous academic webpage HERE.

David Wipf

​​​​​2019

  • Kaixuan Wei, Jiaolong Yang, Ying Fu, David Wipf, and Hua Huang, "Single Image Reflection Removal Exploiting Misaligned Training Data and Network Enhancements," IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2019 (to appear).

  • Bin Dai and David Wipf, "Diagnosing and Enhancing VAE Models," International Conference on Learning Representations (ICLR), 2019.


2018


2017



2016



2015



2014



2013



2012


  • Liwei Wang, Yin Li, Jiaya Jia, Jian Sun, David Wipf, and James Rehg, "Learning Sparse Covariance Patterns for Natural Scenes," IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2012.

  • David Wipf and Yi Wu, "Dual-Space Analysis of the Sparse Linear Model," Advances in Neural Information Processing Systems (NIPS), 2012.

  • David Wipf, "Non-Convex Rank Minimization via an Empirical Bayesian Approach," Uncertainty in Artificial Intelligence (UAI), 2012.

  • Satoshi Ikehata, David Wipf, Yasuyuki Matsushita, and Kiyoharu Aizawa, "Robust Photometric Stereo using Sparse Regression," IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2012.

  • Julia Owen, David Wipf, Hagai Attias, Kensuke Sekihara, and Srikantan Nagarajan, "Performance evaluation of the Champagne source reconstruction algorithm on simulated and real M/EEG data," NeuroImage, 2012.


2011


  • David Wipf, Bhaskar Rao, and Srikantan Nagarajan, "Latent Variable Bayesian Models for Promoting Sparsity," IEEE Transactions of Information Theory, 2011.

  • David Wipf, "Sparse Estimation with Structured Dictionaries," Advances in Neural Information Processing Systems (NIPS), 2011.