David P. Wipf - RankMe

97 papers A* 24A 6B 1Misc 1Journal 40Unranked 24

Year	Rank	Type	Title / Venue / Authors
2022	A*	`conf`	Descent Steps of a Relation-Aware Energy Produce Heterogeneous Graph Neural Networks. NeurIPS Hongjoon Ahn, Yongyi Yang, Quan Gan, Taesup Moon, David P. Wipf
2022	A*	`conf`	Learning Enhanced Representation for Tabular Data via Neighborhood Propagation. NeurIPS Kounianhua Du, Weinan Zhang, Ruiwen Zhou, Yangkun Wang, Xilong Zhao, Jiarui Jin, Quan Gan, Zheng Zhang, David P. Wipf
2022	A*	`conf`	Learning Manifold Dimensions with Conditional Variational Autoencoders. NeurIPS Yijia Zheng, Tong He, Yixuan Qiu, David P. Wipf
2022	A*	`conf`	NodeFormer: A Scalable Graph Structure Learning Transformer for Node Classification. NeurIPS Qitian Wu, Wentao Zhao, Zenan Li, David P. Wipf, Junchi Yan
2022	A*	`conf`	Self-supervised Amodal Video Object Segmentation. NeurIPS Jian Yao, Yuxin Hong, Chiyu Wang, Tianjun Xiao, Tong He, Francesco Locatello, David P. Wipf, Yanwei Fu, Zheng Zhang
2022	A*	`conf`	Transformers from an Optimization Perspective. NeurIPS Yongyi Yang, Zengfeng Huang, David P. Wipf
2021	A*	`conf`	On the Value of Infinite Gradients in Variational Autoencoder Models. NeurIPS Bin Dai, Wenliang Li, David P. Wipf
2020	A*	`conf`	Further Analysis of Outlier Detection with Deep Generative Models. NeurIPS Ziyu Wang, Bin Dai, David P. Wipf, Jun Zhu
2020	J	`jnl`	Further Analysis of Outlier Detection with Deep Generative Models. CoRR Ziyu Wang, Bin Dai, David P. Wipf, Jun Zhu
2020	A*	`conf`	The Usual Suspects? Reassessing Blame for VAE Posterior Collapse. ICML Bin Dai, Ziyu Wang, David P. Wipf
2019	—	`conf`	Diagnosing and Enhancing VAE Models. ICLR (Poster) Bin Dai, David P. Wipf
2019	J	`jnl`	Diagnosing and Enhancing VAE Models. CoRR Bin Dai, David P. Wipf
2019	A*	`conf`	Face Video Deblurring Using 3D Facial Priors. ICCV Wenqi Ren, Jiaolong Yang, Senyou Deng, David P. Wipf, Xiaochun Cao, Xin Tong
2019	A*	`conf`	Single Image Reflection Removal Exploiting Misaligned Training Data and Network Enhancements. CVPR Kaixuan Wei, Jiaolong Yang, Ying Fu, David P. Wipf, Hua Huang
2019	J	`jnl`	Single Image Reflection Removal Exploiting Misaligned Training Data and Network Enhancements. CoRR Kaixuan Wei, Jiaolong Yang, Ying Fu, David P. Wipf, Hua Huang
2019	J	`jnl`	The Usual Suspects? Reassessing Blame for VAE Posterior Collapse. CoRR Bin Dai, Ziyu Wang, David P. Wipf
2018	J	`jnl`	Building Invariances Into Sparse Subspace Clustering. IEEE Trans. Signal Process. Bo Xin, Yizhou Wang, Wen Gao, David P. Wipf
2018	A*	`conf`	Compressing Neural Networks using the Variational Information Bottleneck. ICML Bin Dai, Chen Zhu, Baining Guo, David P. Wipf
2018	J	`jnl`	Compressing Neural Networks using the Variational Information Bottleneck. CoRR Bin Dai, Chen Zhu, David P. Wipf
2018	J	`jnl`	Connections with Robust PCA and the Role of Emergent Sparsity in Variational Autoencoder Models. J. Mach. Learn. Res. Bin Dai, Yu Wang, John A. D. Aston, Gang Hua, David P. Wipf
2018	J	`jnl`	Image Smoothing via Unsupervised Learning. CoRR Qingnan Fan, Jiaolong Yang, David P. Wipf, Baoquan Chen, Xin Tong
2018	J	`jnl`	Image smoothing via unsupervised learning. ACM Trans. Graph. Qingnan Fan, Jiaolong Yang, David P. Wipf, Baoquan Chen, Xin Tong
2018	J	`jnl`	Recurrent Variational Autoencoders for Learning Nonlinear Generative Models in the Presence of Outliers. IEEE J. Sel. Top. Signal Process. Yu Wang, Bin Dai, Gang Hua, John A. D. Aston, David P. Wipf
2018	A*	`conf`	Revisiting Deep Intrinsic Image Decompositions. CVPR Qingnan Fan, Jiaolong Yang, Gang Hua, Baoquan Chen, David P. Wipf
2017	A*	`conf`	A Generic Deep Architecture for Single Image Reflection Removal and Image Smoothing. ICCV Qingnan Fan, Jiaolong Yang, Gang Hua, Baoquan Chen, David P. Wipf
2017	J	`jnl`	A Generic Deep Architecture for Single Image Reflection Removal and Image Smoothing. CoRR Qingnan Fan, Jiaolong Yang, Gang Hua, Baoquan Chen, David P. Wipf
2017	J	`jnl`	An Efficient Joint Formulation for Bayesian Face Verification. IEEE Trans. Pattern Anal. Mach. Intell. Dong Chen, Xudong Cao, David P. Wipf, Fang Wen, Jian Sun
2017	A	`conf`	Data-Dependent Sparsity for Subspace Clustering. UAI Bo Xin, Yizhou Wang, Wen Gao, David P. Wipf
2017	—	`conf`	From Bayesian Sparsity to Gated Recurrent Nets. NIPS Hao He, Bo Xin, Satoshi Ikehata, David P. Wipf
2017	J	`jnl`	From Bayesian Sparsity to Gated Recurrent Nets. CoRR Hao He, Bo Xin, David P. Wipf
2017	A	`conf`	Green Generative Modeling: Recycling Dirty Data using Recurrent Variational Autoencoders. UAI Yu Wang, Bin Dai, Gang Hua, John A. D. Aston, David P. Wipf
2017	J	`jnl`	Revisiting Deep Image Smoothing and Intrinsic Image Decomposition. CoRR Qingnan Fan, David P. Wipf, Gang Hua, Baoquan Chen
2017	J	`jnl`	Veiled Attributes of the Variational Autoencoder. CoRR Bin Dai, Yu Wang, John A. D. Aston, Gang Hua, David P. Wipf
2016	—	`conf`	A Pseudo-Bayesian Algorithm for Robust PCA. NIPS Tae-Hyun Oh, Yasuyuki Matsushita, In-So Kweon, David P. Wipf
2016	A*	`conf`	Analysis of Variational Bayesian Factorizations for Sparse and Low-Rank Estimation. ICML David P. Wipf
2016	J	`jnl`	Exploring Algorithmic Limits of Matrix Rank Minimization Under Affine Constraints. IEEE Trans. Signal Process. Bo Xin, Yizhou Wang, Wen Gao, David P. Wipf
2016	A*	`conf`	Improving Survey Aggregation with Sparsely Represented Signals. KDD Tianlin Shi, Forest Agostinelli, Matthew Staib, David P. Wipf, Thomas Moscibroda
2016	—	`conf`	Maximal Sparsity with Deep Networks? NIPS Bo Xin, Yizhou Wang, Wen Gao, David P. Wipf, Baoyuan Wang
2016	J	`jnl`	Maximal Sparsity with Deep Networks? CoRR Bo Xin, Yizhou Wang, Wen Gao, David P. Wipf
2016	J	`jnl`	Simultaneous Bayesian Sparse Approximation With Structured Sparse Models. IEEE Trans. Signal Process. Wei Chen, David P. Wipf, Yu Wang, Yang Liu, Ian J. Wassell
2016	J	`jnl`	Sparse-as-possible SVBRDF acquisition. ACM Trans. Graph. Zhiming Zhou, Guojun Chen, Yue Dong, David P. Wipf, Yong Yu, John M. Snyder, Xin Tong
2016	A	`conf`	Subspace Clustering with a Twist. UAI David P. Wipf, Yue Dong, Bo Xin
2015	B	`conf`	Augmented Bayesian Compressive Sensing. DCC David P. Wipf, Jeong-Min Yun, Qing Ling
2015	A	`conf`	Clustered Sparse Bayesian Learning. UAI Yu Wang, David P. Wipf, Jeong-Min Yun, Wei Chen, Ian J. Wassell
2015	A*	`conf`	Multi-Task Learning for Subspace Segmentation. ICML Yu Wang, David P. Wipf, Qing Ling, Wei Chen, Ian J. Wassell
2015	J	`jnl`	New Design Criteria for Robust PCA and a Compliant Bayesian-Inspired Algorithm. CoRR Tae Hyun Oh, David P. Wipf, Yasuyuki Matsushita, In-So Kweon
2015	A*	`conf`	Pushing the Limits of Affine Rank Minimization by Adapting Probabilistic PCA. ICML Bo Xin, David P. Wipf
2015	A	`conf`	Understanding and Evaluating Sparse Linear Discriminant Analysis. AISTATS Yi Wu, David P. Wipf, Jeong-Min Yun
2015	J	`jnl`	Unsupervised Extraction of Video Highlights Via Robust Recurrent Auto-encoders. CoRR Huan Yang, Baoyuan Wang, Stephen Lin, David P. Wipf, Minyi Guo, Baining Guo
2015	A*	`conf`	Unsupervised Extraction of Video Highlights via Robust Recurrent Auto-Encoders. ICCV Huan Yang, Baoyuan Wang, Stephen Lin, David P. Wipf, Minyi Guo, Baining Guo
2014	Misc	`conf`	Exploiting the convex-concave penalty for tracking: A novel dynamic reweighted sparse Bayesian learning algorithm. ICASSP Yu Wang, David P. Wipf, Wei Chen, Ian J. Wassell
2014	J	`jnl`	Exploring Algorithmic Limits of Matrix Rank Minimization under Affine Constraints. CoRR Bo Xin, David P. Wipf
2014	J	`jnl`	Multi-Observation Blind Deconvolution with an Adaptive Sparse Prior. IEEE Trans. Pattern Anal. Mach. Intell. Haichao Zhang, David P. Wipf, Yanning Zhang
2014	J	`jnl`	Non-Convex Rank Minimization via an Empirical Bayesian Approach. CoRR David P. Wipf
2014	J	`jnl`	Photometric Stereo Using Sparse Bayesian Regression for General Diffuse Surfaces. IEEE Trans. Pattern Anal. Mach. Intell. Satoshi Ikehata, David P. Wipf, Yasuyuki Matsushita, Kiyoharu Aizawa
2014	J	`jnl`	Revisiting Bayesian blind deconvolution. J. Mach. Learn. Res. David P. Wipf, Haichao Zhang
2013	A*	`conf`	A Practical Transfer Learning Algorithm for Face Verification. ICCV Xudong Cao, David P. Wipf, Fang Wen, Genquan Duan, Jian Sun
2013	—	`conf`	A hierarchical Bayesian M/EEG imagingmethod correcting for incomplete spatio-temporal priors. ISBI Carsten Stahlhut, Hagai Thomas Attias, Kensuke Sekihara, David P. Wipf, Lars Kai Hansen, Srikantan S. Nagarajan
2013	—	`conf`	Analysis of Bayesian Blind Deconvolution. EMMCVPR David P. Wipf, Haichao Zhang
2013	—	`conf`	Fixed-Point Model For Structured Labeling. ICML (1) Quannan Li, Jingdong Wang, David P. Wipf, Zhuowen Tu
2013	A*	`conf`	Multi-image Blind Deblurring Using a Coupled Adaptive Sparse Prior. CVPR Haichao Zhang, David P. Wipf, Yanning Zhang
2013	J	`jnl`	Non-Uniform Blind Deblurring with a Spatially-Adaptive Sparse Prior. CoRR Haichao Zhang, David P. Wipf
2013	—	`conf`	Non-Uniform Camera Shake Removal Using a Spatially-Adaptive Sparse Penalty. NIPS Haichao Zhang, David P. Wipf
2013	J	`jnl`	Revisiting Bayesian Blind Deconvolution CoRR David P. Wipf, Haichao Zhang
2012	J	`jnl`	Dual-Space Analysis of the Sparse Linear Model CoRR David P. Wipf, Yi Wu
2012	—	`conf`	Dual-Space Analysis of the Sparse Linear Model. NIPS David P. Wipf, Yi Wu
2012	J	`jnl`	Image Super-Resolution via Sparse Bayesian Modeling of Natural Images CoRR Haichao Zhang, David P. Wipf, Yanning Zhang
2012	A*	`conf`	Learning sparse covariance patterns for natural scenes. CVPR Liwei Wang, Yin Li, Jiaya Jia, Jian Sun, David P. Wipf, James M. Rehg
2012	J	`jnl`	Non-Convex Rank Minimization via an Empirical Bayesian Approach CoRR David P. Wipf
2012	A	`conf`	Non-Convex Rank Minimization via an Empirical Bayesian Approach. UAI David P. Wipf
2012	J	`jnl`	Performance evaluation of the Champagne source reconstruction algorithm on simulated and real M/EEG data. NeuroImage Julia P. Owen, David P. Wipf, Hagai Thomas Attias, Kensuke Sekihara, Srikantan S. Nagarajan
2012	A*	`conf`	Robust photometric stereo using sparse regression. CVPR Satoshi Ikehata, David P. Wipf, Yasuyuki Matsushita, Kiyoharu Aizawa
2011	J	`jnl`	Latent Variable Bayesian Models for Promoting Sparsity. IEEE Trans. Inf. Theory David P. Wipf, Bhaskar D. Rao, Srikantan S. Nagarajan
2011	—	`conf`	Sparse Estimation with Structured Dictionaries. NIPS David P. Wipf
2010	J	`jnl`	Iterative Reweighted IEEE J. Sel. Top. Signal Process. David P. Wipf, Srikantan S. Nagarajan
2010	J	`jnl`	Robust Bayesian estimation of the location, orientation, and time course of multiple correlated neural sources using MEG. NeuroImage David P. Wipf, Julia P. Owen, Hagai Thomas Attias, Kensuke Sekihara, Srikantan S. Nagarajan
2010	—	`conf`	Sparse Spatio-temporal Inference of Electromagnetic Brain Sources. MLMI Carsten Stahlhut, Hagai Attias, David P. Wipf, Lars Kai Hansen, Srikantan S. Nagarajan
2010	J	`jnl`	Variational Bayesian Inference Techniques. IEEE Signal Process. Mag. Matthias W. Seeger, David P. Wipf
2009	J	`jnl`	A unified Bayesian framework for MEG/EEG source imaging. NeuroImage David P. Wipf, Srikantan S. Nagarajan
2009	—	`conf`	Robust Methods for Reconstructing Brain Activity and Functional Connectivity Between Brain Sources with MEG/EEG Data. ISBI Julia P. Owen, David P. Wipf, Hagai Attias, Kensuke Sekihara, Srikantan S. Nagarajan
2009	—	`conf`	Sparse Estimation Using General Likelihoods and Non-Factorial Priors. NIPS David P. Wipf, Srikantan S. Nagarajan
2008	—	`conf`	Estimating the Location and Orientation of Complex, Correlated Neural Activity using MEG. NIPS David P. Wipf, Julia P. Owen, Hagai Attias, Kensuke Sekihara, Srikantan S. Nagarajan
2007	—	`conf`	A New View of Automatic Relevance Determination. NIPS David P. Wipf, Srikantan S. Nagarajan
2007	J	`jnl`	An Empirical Bayesian Strategy for Solving the Simultaneous Sparse Approximation Problem. IEEE Trans. Signal Process. David P. Wipf, Bhaskar D. Rao
2007	A*	`conf`	Beamforming using the relevance vector machine. ICML David P. Wipf, Srikantan S. Nagarajan
2007	J	`jnl`	Lane Change Intent Analysis Using Robust Operators and Sparse Bayesian Learning. IEEE Trans. Intell. Transp. Syst. Joel C. McCall, David P. Wipf, Mohan M. Trivedi, Bhaskar D. Rao
2007	—	`conf`	Performance Evaluation of Latent Variable Models with Sparse Priors. ICASSP (2) David P. Wipf, Jason A. Palmer, Bhaskar D. Rao, Kenneth Kreutz-Delgado
2006	—	`conf`	Analysis of Empirical Bayesian Methods for Neuroelectromagnetic Source Localization. NIPS David P. Wipf, Rey Ramírez, Jason A. Palmer, Scott Makeig, Bhaskar D. Rao
2006	—	`—`	Bayesian methods for finding sparse representations. David P. Wipf
2005	—	`conf`	Comparing the Effects of Different Weight Distributions on Finding Sparse Representations. NIPS David P. Wipf, Bhaskar D. Rao
2005	—	`conf`	Lane Change Intent Analysis Using Robust Operators and Sparse Bayesian Learning. CVPR Workshops Joel C. McCall, Mohan M. Trivedi, David P. Wipf, Bhaskar D. Rao
2005	—	`conf`	Variational EM Algorithms for Non-Gaussian Latent Variable Models. NIPS Jason A. Palmer, David P. Wipf, Kenneth Kreutz-Delgado, Bhaskar D. Rao
2004	—	`conf`	L_0-norm Minimization for Basis Selection. NIPS David P. Wipf, Bhaskar D. Rao
2004	—	`conf`	Probabilistic analysis for basis selection via ℓ ICASSP (2) David P. Wipf, Bhaskar D. Rao
2004	J	`jnl`	Sparse Bayesian learning for basis selection. IEEE Trans. Signal Process. David P. Wipf, Bhaskar D. Rao
2003	—	`conf`	Bayesian learning for sparse signal reconstruction. ICASSP (6) David P. Wipf, Bhaskar D. Rao
2003	—	`conf`	Perspectives on Sparse Bayesian Learning. NIPS David P. Wipf, Jason A. Palmer, Bhaskar D. Rao