John W. Paisley

126 papers A* 23A 6B 6C 1Misc 4Journal 75Unranked 10

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Fully Bayesian differential Gaussian processes through stochastic differential equations. Knowl. Based Syst. Jian Xu, Zhiqi Lin, Min Chen, Junmei Yang, Delu Zeng, John W. Paisley
2024	J	`jnl`	Entropy-Informed Weighting Channel Normalizing Flow. CoRR Wei Chen, Shian Du, Shigui Li, Delu Zeng, John W. Paisley
2024	J	`jnl`	Flexible Bayesian Last Layer Models Using Implicit Priors and Diffusion Posterior Sampling. CoRR Jian Xu, Zhiqi Lin, Shigui Li, Min Chen, Junmei Yang, Delu Zeng, John W. Paisley
2024	J	`jnl`	Fully Bayesian Differential Gaussian Processes through Stochastic Differential Equations. CoRR Jian Xu, Zhiqi Lin, Min Chen, Junmei Yang, Delu Zeng, John W. Paisley
2024	J	`jnl`	Information Geometry and Beta Link for Optimizing Sparse Variational Student-t Processes. CoRR Jian Xu, Delu Zeng, John W. Paisley
2024	A*	`conf`	Sparse Inducing Points in Deep Gaussian Processes: Enhancing Modeling with Denoising Diffusion Variational Inference. ICML Jian Xu, Delu Zeng, John W. Paisley
2024	J	`jnl`	Sparse Inducing Points in Deep Gaussian Processes: Enhancing Modeling with Denoising Diffusion Variational Inference. CoRR Jian Xu, Delu Zeng, John W. Paisley
2023	J	`jnl`	A Multiscale Approach to Deep Blind Image Quality Assessment. IEEE Trans. Image Process. Manni Liu, Jiabin Huang, Delu Zeng, Xinghao Ding, John W. Paisley
2023	J	`jnl`	Double Normalizing Flows: Flexible Bayesian Gaussian Process ODEs Learning. CoRR Jian Xu, Shian Du, Junmei Yang, Xinghao Ding, John W. Paisley, Delu Zeng
2023	J	`jnl`	Learning Rate Dropout. IEEE Trans. Neural Networks Learn. Syst. Huangxing Lin, Weihong Zeng, Yihong Zhuang, Xinghao Ding, Yue Huang, John W. Paisley
2023	J	`jnl`	Nonlinear Kalman Filtering with Reparametrization Gradients. CoRR San Gultekin, Brendan Kitts, Aaron Flores, John W. Paisley
2023	A*	`conf`	Self-Supervised Image Denoising Using Implicit Deep Denoiser Prior. AAAI Huangxing Lin, Yihong Zhuang, Xinghao Ding, Delu Zeng, Yue Huang, Xiaotong Tu, John W. Paisley
2022	B	`conf`	Bayesian Nonparametric Model Averaging Using Scalable Gaussian Process Representations. IEEE Big Data John W. Paisley, Sebastian Rowland, Jeremiah Zhe Liu, Brent A. Coull, Marianthi-Anna Kioumourtzoglou
2022	J	`jnl`	Few-shot medical image segmentation using a global correlation network with discriminative embedding. Comput. Biol. Medicine Liyan Sun, Chenxin Li, Xinghao Ding, Yue Huang, Zhong Chen, Guisheng Wang, Yizhou Yu, John W. Paisley
2022	B	`conf`	Probabilistic Orthogonal Matching Pursuit. IEEE Big Data Ghazal Fazelnia, John W. Paisley
2021	J	`jnl`	Deep Multiscale Detail Networks for Multiband Spectral Image Sharpening. IEEE Trans. Neural Networks Learn. Syst. Xueyang Fu, Wu Wang, Yue Huang, Xinghao Ding, John W. Paisley
2021	J	`jnl`	Self-Verification in Image Denoising. CoRR Huangxing Lin, Yihong Zhuang, Delu Zeng, Yue Huang, Xinghao Ding, John W. Paisley
2021	J	`jnl`	Successive Graph Convolutional Network for Image De-raining. Int. J. Comput. Vis. Xueyang Fu, Qi Qi, Zheng-Jun Zha, Xinghao Ding, Feng Wu, John W. Paisley
2020	J	`jnl`	A 3D Spatially Weighted Network for Segmentation of Brain Tissue From MRI. IEEE Trans. Medical Imaging Liyan Sun, Wenao Ma, Xinghao Ding, Yue Huang, Dong Liang, John W. Paisley
2020	J	`jnl`	A dual-domain deep lattice network for rapid MRI reconstruction. Neurocomputing Liyan Sun, Yawen Wu, Binglin Shu, Xinghao Ding, Congbo Cai, Yue Huang, John W. Paisley
2020	J	`jnl`	Adaptive noise imitation for image denoising. CoRR Huangxing Lin, Yihong Zhuang, Yue Huang, Xinghao Ding, Yizhou Yu, Xiaoqing Liu, John W. Paisley
2020	J	`jnl`	An Adversarial Learning Approach to Medical Image Synthesis for Lesion Detection. IEEE J. Biomed. Health Informatics Liyan Sun, Jiexiang Wang, Yue Huang, Xinghao Ding, Hayit Greenspan, John W. Paisley
2020	J	`jnl`	Bayesian recurrent state space model for rs-fMRI. CoRR Arunesh Mittal, Scott W. Linderman, John W. Paisley, Paul Sajda
2020	J	`jnl`	Deep Bayesian Nonparametric Factor Analysis. CoRR Arunesh Mittal, Paul Sajda, John W. Paisley
2020	J	`jnl`	Lightweight Pyramid Networks for Image Deraining. IEEE Trans. Neural Networks Learn. Syst. Xueyang Fu, Borong Liang, Yue Huang, Xinghao Ding, John W. Paisley
2020	J	`jnl`	MBA: Mini-Batch AUC Optimization. IEEE Trans. Neural Networks Learn. Syst. San Gultekin, Avishek Saha, Adwait Ratnaparkhi, John W. Paisley
2020	—	`conf`	Mixed membership recurrent neural networks for modeling customer purchases. ICAIF Ghazal Fazelnia, Mark Ibrahim, Ceena Modarres, Kevin Wu, John W. Paisley
2020	J	`jnl`	Rain O'er Me: Synthesizing Real Rain to Derain With Data Distillation. IEEE Trans. Image Process. Huangxing Lin, Yanlong Li, Xueyang Fu, Xinghao Ding, Yue Huang, John W. Paisley
2020	A	`conf`	Risk Bounds for Low Cost Bipartite Ranking. UAI San Gultekin, John W. Paisley
2019	A*	`conf`	A state-space model for inferring effective connectivity of latent neural dynamics from simultaneous EEG/fMRI. NeurIPS Tao Tu, John W. Paisley, Stefan Haufe, Paul Sajda
2019	A*	`conf`	Accurate Uncertainty Estimation and Decomposition in Ensemble Learning. NeurIPS Jeremiah Z. Liu, John W. Paisley, Marianthi-Anna Kioumourtzoglou, Brent A. Coull
2019	J	`jnl`	Accurate Uncertainty Estimation and Decomposition in Ensemble Learning. CoRR Jeremiah Zhe Liu, John W. Paisley, Marianthi-Anna Kioumourtzoglou, Brent A. Coull
2019	A*	`conf`	Deep Blind Hyperspectral Image Fusion. ICCV Wu Wang, Weihong Zeng, Yue Huang, Xinghao Ding, John W. Paisley
2019	Misc	`conf`	Fully Supervised Speaker Diarization. ICASSP Aonan Zhang, Quan Wang, Zhenyao Zhu, John W. Paisley, Chong Wang
2019	C	`conf`	Global Explanations of Neural Networks: Mapping the Landscape of Predictions. AIES Mark Ibrahim, Melissa Louie, Ceena Modarres, John W. Paisley
2019	J	`jnl`	Global Explanations of Neural Networks: Mapping the Landscape of Predictions. CoRR Mark Ibrahim, Melissa Louie, Ceena Modarres, John W. Paisley
2019	A*	`conf`	JPEG Artifacts Reduction via Deep Convolutional Sparse Coding. ICCV Xueyang Fu, Zheng-Jun Zha, Feng Wu, Xinghao Ding, John W. Paisley
2019	—	`conf`	Joint CS-MRI Reconstruction and Segmentation with a Unified Deep Network. IPMI Liyan Sun, Zhiwen Fan, Xinghao Ding, Yue Huang, John W. Paisley
2019	J	`jnl`	Learning Rate Dropout. CoRR Huangxing Lin, Weihong Zeng, Xinghao Ding, Yue Huang, Chenxi Huang, John W. Paisley
2019	J	`jnl`	Noise2Blur: Online Noise Extraction and Denoising. CoRR Huangxing Lin, Weihong Zeng, Xinghao Ding, Xueyang Fu, Yue Huang, John W. Paisley
2019	J	`jnl`	Online Forecasting Matrix Factorization. IEEE Trans. Signal Process. San Gultekin, John W. Paisley
2019	J	`jnl`	Rain O'er Me: Synthesizing real rain to derain with data distillation. CoRR Huangxing Lin, Yanlong Li, Xinghao Ding, Weihong Zeng, Yue Huang, John W. Paisley
2019	A*	`conf`	Random Function Priors for Correlation Modeling. ICML Aonan Zhang, John W. Paisley
2019	J	`jnl`	Random Function Priors for Correlation Modeling. CoRR Aonan Zhang, John W. Paisley
2019	J	`jnl`	Reweighted Expectation Maximization. CoRR Adji B. Dieng, John W. Paisley
2019	J	`jnl`	Risk Bounds for Low Cost Bipartite Ranking. CoRR San Gultekin, John W. Paisley
2018	J	`jnl`	A Deep Error Correction Network for Compressed Sensing MRI. CoRR Liyan Sun, Zhiwen Fan, Yue Huang, Xinghao Ding, John W. Paisley
2018	J	`jnl`	A Deep Information Sharing Network for Multi-contrast Compressed Sensing MRI Reconstruction. CoRR Liyan Sun, Zhiwen Fan, Yue Huang, Xinghao Ding, John W. Paisley
2018	J	`jnl`	A Deep Tree-Structured Fusion Model for Single Image Deraining. CoRR Xueyang Fu, Qi Qi, Yue Huang, Xinghao Ding, Feng Wu, John W. Paisley
2018	J	`jnl`	A Divide-and-Conquer Approach to Compressed Sensing MRI. CoRR Liyan Sun, Zhiwen Fan, Xinghao Ding, Congbo Cai, Yue Huang, John W. Paisley
2018	J	`jnl`	A Modified EM Algorithm for ISAR Scatterer Trajectory Matrix Completion. IEEE Trans. Geosci. Remote. Sens. Lei Liu, Feng Zhou, Xueru Bai, John W. Paisley, Hongbing Ji
2018	—	`conf`	A Segmentation-Aware Deep Fusion Network for Compressed Sensing MRI. ECCV (6) Zhiwen Fan, Liyan Sun, Xinghao Ding, Yue Huang, Congbo Cai, John W. Paisley
2018	J	`jnl`	A Segmentation-aware Deep Fusion Network for Compressed Sensing MRI. CoRR Zhiwen Fan, Liyan Sun, Xinghao Ding, Yue Huang, Congbo Cai, John W. Paisley
2018	J	`jnl`	Adaptive and Calibrated Ensemble Learning with Dependent Tail-free Process. CoRR Jeremiah Zhe Liu, John W. Paisley, Marianthi-Anna Kioumourtzoglou, Brent A. Coull
2018	J	`jnl`	An Adversarial Learning Approach to Medical Image Synthesis for Lesion Removal. CoRR Liyan Sun, Jiexiang Wang, Xinghao Ding, Yue Huang, John W. Paisley
2018	B	`conf`	Asymptotic Simulated Annealing for Variational Inference. GLOBECOM San Gultekin, Aonan Zhang, John W. Paisley
2018	A*	`conf`	CRVI: Convex Relaxation for Variational Inference. ICML Ghazal Fazelnia, John W. Paisley
2018	A*	`conf`	Compressed Sensing MRI Using a Recursive Dilated Network. AAAI Liyan Sun, Zhiwen Fan, Yue Huang, Xinghao Ding, John W. Paisley
2018	A*	`conf`	Deep Bayesian Nonparametric Tracking. ICML Aonan Zhang, John W. Paisley
2018	J	`jnl`	Fully Supervised Speaker Diarization. CoRR Aonan Zhang, Quan Wang, Zhenyao Zhu, John W. Paisley, Chong Wang
2018	J	`jnl`	Hyperspectral Image Classification With Markov Random Fields and a Convolutional Neural Network. IEEE Trans. Image Process. Xiangyong Cao, Feng Zhou, Lin Xu, Deyu Meng, Zongben Xu, John W. Paisley
2018	J	`jnl`	Joint CS-MRI Reconstruction and Segmentation with a Unified Deep Network. CoRR Liyan Sun, Zhiwen Fan, Yue Huang, Xinghao Ding, John W. Paisley
2018	J	`jnl`	Lightweight Pyramid Networks for Image Deraining. CoRR Xueyang Fu, Borong Liang, Yue Huang, Xinghao Ding, John W. Paisley
2018	J	`jnl`	MBA: Mini-Batch AUC Optimization. CoRR San Gultekin, Avishek Saha, Adwait Ratnaparkhi, John W. Paisley
2018	A*	`conf`	MEnet: A Metric Expression Network for Salient Object Segmentation. IJCAI Shulian Cai, Jiabin Huang, Delu Zeng, Xinghao Ding, John W. Paisley
2018	J	`jnl`	MEnet: A Metric Expression Network for Salient Object Segmentation. CoRR Shulian Cai, Jiabin Huang, Delu Zeng, Xinghao Ding, John W. Paisley
2018	J	`jnl`	Mixed Membership Recurrent Neural Networks. CoRR Ghazal Fazelnia, Mark Ibrahim, Ceena Modarres, Kevin Wu, John W. Paisley
2018	J	`jnl`	Towards Explainable Deep Learning for Credit Lending: A Case Study. CoRR Ceena Modarres, Mark Ibrahim, Melissa Louie, John W. Paisley
2017	J	`jnl`	Clearing the Skies: A Deep Network Architecture for Single-Image Rain Removal. IEEE Trans. Image Process. Xueyang Fu, Jiabin Huang, Xinghao Ding, Yinghao Liao, John W. Paisley
2017	J	`jnl`	Hyperspectral Image Segmentation with Markov Random Fields and a Convolutional Neural Network. CoRR Xiangyong Cao, Feng Zhou, Lin Xu, Deyu Meng, Zongben Xu, John W. Paisley
2017	—	`conf`	Location Dependent Dirichlet Processes. IScIDE Shiliang Sun, John W. Paisley, Qiuyang Liu
2017	J	`jnl`	Location Dependent Dirichlet Processes. CoRR Shiliang Sun, John W. Paisley, Qiuyang Liu
2017	J	`jnl`	Nonlinear Kalman Filtering With Divergence Minimization. IEEE Trans. Signal Process. San Gultekin, John W. Paisley
2017	J	`jnl`	Online Forecasting Matrix Factorization. CoRR San Gultekin, John W. Paisley
2017	A*	`conf`	PanNet: A Deep Network Architecture for Pan-Sharpening. ICCV Junfeng Yang, Xueyang Fu, Yuwen Hu, Yue Huang, Xinghao Ding, John W. Paisley
2017	A*	`conf`	Removing Rain from Single Images via a Deep Detail Network. CVPR Xueyang Fu, Jiabin Huang, Delu Zeng, Yue Huang, Xinghao Ding, John W. Paisley
2017	J	`jnl`	Revealing common disease mechanisms shared by tumors of different tissues of origin through semantic representation of genomic alterations and topic modeling. BMC Genom. Vicky Chen, John W. Paisley, Xinghua Lu
2017	—	`conf`	TopicRNN: A Recurrent Neural Network with Long-Range Semantic Dependency. ICLR (Poster) Adji B. Dieng, Chong Wang, Jianfeng Gao, John W. Paisley
2017	—	`conf`	Variational Inference via \chi Upper Bound Minimization. NIPS Adji Bousso Dieng, Dustin Tran, Rajesh Ranganath, John W. Paisley, David M. Blei
2016	J	`jnl`	A fusion-based enhancing method for weakly illuminated images. Signal Process. Xueyang Fu, Delu Zeng, Yue Huang, Yinghao Liao, Xinghao Ding, John W. Paisley
2016	J	`jnl`	Clearing the Skies: A deep network architecture for single-image rain removal. CoRR Xueyang Fu, Jiabin Huang, Xinghao Ding, Yinghao Liao, John W. Paisley
2016	A*	`conf`	Markov Latent Feature Models. ICML Aonan Zhang, John W. Paisley
2016	A	`conf`	Stochastic Variational Inference for the HDP-HMM. AISTATS Aonan Zhang, San Gultekin, John W. Paisley
2016	J	`jnl`	The $χ$-Divergence for Approximate Inference. CoRR Adji B. Dieng, Dustin Tran, Rajesh Ranganath, John W. Paisley, David M. Blei
2016	J	`jnl`	TopicRNN: A Recurrent Neural Network with Long-Range Semantic Dependency. CoRR Adji B. Dieng, Chong Wang, Jianfeng Gao, John W. Paisley
2015	J	`jnl`	A Collaborative Kalman Filter for Time-Evolving Dyadic Processes. CoRR San Gultekin, John W. Paisley
2015	A*	`conf`	Bayesian Poisson Tensor Factorization for Inferring Multilateral Relations from Sparse Dyadic Event Counts. KDD Aaron Schein, John W. Paisley, David M. Blei, Hanna M. Wallach
2015	J	`jnl`	Bayesian Poisson Tensor Factorization for Inferring Multilateral Relations from Sparse Dyadic Event Counts. CoRR Aaron Schein, John W. Paisley, David M. Blei, Hanna M. Wallach
2015	J	`jnl`	Combinatorial Clustering and the Beta Negative Binomial Process. IEEE Trans. Pattern Anal. Mach. Intell. Tamara Broderick, Lester W. Mackey, John W. Paisley, Michael I. Jordan
2015	A*	`conf`	Landmarking Manifolds with Gaussian Processes. ICML Dawen Liang, John W. Paisley
2015	A*	`conf`	Markov Mixed Membership Models. ICML Aonan Zhang, John W. Paisley
2015	J	`jnl`	Nested Hierarchical Dirichlet Processes. IEEE Trans. Pattern Anal. Mach. Intell. John W. Paisley, Chong Wang, David M. Blei, Michael I. Jordan
2015	A*	`conf`	Pan-Sharpening with a Hyper-Laplacian Penalty. ICCV Yiyong Jiang, Xinghao Ding, Delu Zeng, Yue Huang, John W. Paisley
2015	—	`conf`	Scalable Bayesian nonparametric dictionary learning. EUSIPCO Sarper Sertoglu, John W. Paisley
2014	A*	`conf`	A Collaborative Kalman Filter for Time-Evolving Dyadic Processes. ICDM San Gultekin, John W. Paisley
2014	—	`ch.`	Bayesian Nonnegative Matrix Factorization with Stochastic Variational Inference. Handbook of Mixed Membership Models and Their Applications John W. Paisley, David M. Blei, Michael I. Jordan
2014	J	`jnl`	Bayesian Nonparametric Dictionary Learning for Compressed Sensing MRI. IEEE Trans. Image Process. Yue Huang, John W. Paisley, Qin Lin, Xinghao Ding, Xueyang Fu, Xiao-Ping (Steven) Zhang
2014	—	`conf`	Codebook-based Scalable Music Tagging with Poisson Matrix Factorization. ISMIR Dawen Liang, John W. Paisley, Dan Ellis
2014	A	`conf`	Pan-sharpening with a Bayesian nonparametric dictionary learning model. AISTATS Xinghao Ding, Yiyong Jiang, Yue Huang, John W. Paisley
2013	—	`conf`	A Nested HDP for Hierarchical Topic Models ICLR (Workshop) John W. Paisley, Chong Wang, David M. Blei, Michael I. Jordan
2013	B	`conf`	Compressed sensing MRI with Bayesian dictionary learning. ICIP Xinghao Ding, John W. Paisley, Yue Huang, Xianbo Chen, Feng Huang, Xiao-Ping (Steven) Zhang
2013	J	`jnl`	MR Image Reconstruction from Undersampled k-Space with Bayesian Dictionary Learning CoRR Yue Huang, John W. Paisley, Xianbo Chen, Xinghao Ding, Feng Huang, Xiao-Ping (Steven) Zhang
2013	B	`conf`	Pan-sharpening based on nonparametric Bayesian adaptive dictionary learning. ICIP Jin Xie, Yue Huang, John W. Paisley, Xinghao Ding, Xiao-Ping (Steven) Zhang
2013	J	`jnl`	Stochastic variational inference. J. Mach. Learn. Res. Matthew D. Hoffman, David M. Blei, Chong Wang, John W. Paisley
2012	J	`jnl`	Nested Hierarchical Dirichlet Processes CoRR John W. Paisley, Chong Wang, David M. Blei, Michael I. Jordan
2012	J	`jnl`	Nonparametric Bayesian Dictionary Learning for Analysis of Noisy and Incomplete Images. IEEE Trans. Image Process. Mingyuan Zhou, Haojun Chen, John W. Paisley, Lu Ren, Lingbo Li, Zhengming Xing, David B. Dunson, Guillermo Sapiro, Lawrence Carin
2012	A	`conf`	Stick-Breaking Beta Processes and the Poisson Process. AISTATS John W. Paisley, David M. Blei, Michael I. Jordan
2012	J	`jnl`	Stochastic Variational Inference. CoRR Matthew D. Hoffman, David M. Blei, Chong Wang, John W. Paisley
2012	A*	`conf`	Variational Bayesian Inference with Stochastic Search. ICML John W. Paisley, David M. Blei, Michael I. Jordan
2011	J	`jnl`	Corrections to "Compressive Sensing on Manifolds Using a Nonparametric Mixture of Factor Analyzers: Algorithm and Performance Bounds". IEEE Trans. Signal Process. Minhua Chen, Jorge G. Silva, John W. Paisley, Chunping Wang, David B. Dunson, Lawrence Carin
2011	A	`conf`	Online Variational Inference for the Hierarchical Dirichlet Process. AISTATS Chong Wang, John W. Paisley, David M. Blei
2011	A	`conf`	The Discrete Infinite Logistic Normal Distribution for Mixed-Membership Modeling. AISTATS John W. Paisley, Chong Wang, David M. Blei
2011	A*	`conf`	Variational Inference for Stick-Breaking Beta Process Priors. ICML John W. Paisley, Lawrence Carin, David M. Blei
2010	A*	`conf`	A Stick-Breaking Construction of the Beta Process. ICML John W. Paisley, Aimee K. Zaas, Christopher W. Woods, Geoffrey S. Ginsburg, Lawrence Carin
2010	Misc	`conf`	A nonparametric Bayesian model for kernel matrix completion. ICASSP John W. Paisley, Lawrence Carin
2010	J	`jnl`	Active learning and basis selection for kernel-based linear models: a Bayesian perspective. IEEE Trans. Signal Process. John W. Paisley, Xuejun Liao, Lawrence Carin
2010	J	`jnl`	Bayesian Inference of the Number of Factors in Gene-Expression Analysis: Application to Human Virus Challenge Studies. BMC Bioinform. Bo Chen, Minhua Chen, John W. Paisley, Aimee K. Zaas, Christopher W. Woods, Geoffrey S. Ginsburg, Alfred O. Hero III, Joseph E. Lucas, David B. Dunson, Lawrence Carin
2010	J	`jnl`	Compressive Sensing on Manifolds Using a Nonparametric Mixture of Factor Analyzers: Algorithm and Performance Bounds. IEEE Trans. Signal Process. Minhua Chen, Jorge G. Silva, John W. Paisley, Chunping Wang, David B. Dunson, Lawrence Carin
2010	J	`jnl`	Hierarchical Bayesian Modeling of Topics in Time-Stamped Documents. IEEE Trans. Pattern Anal. Mach. Intell. Iulian Pruteanu-Malinici, Lu Ren, John W. Paisley, Eric Wang, Lawrence Carin
2010	B	`conf`	Nonparametric image interpolation and dictionary learning using spatially-dependent Dirichlet and beta process priors. ICIP John W. Paisley, Mingyuan Zhou, Guillermo Sapiro, Lawrence Carin
2010	Misc	`conf`	Sparse linear regression with beta process priors. ICASSP Bo Chen, John W. Paisley, Lawrence Carin
2009	Misc	`conf`	Dirichlet process mixture models with multiple modalities. ICASSP John W. Paisley, Lawrence Carin
2009	J	`jnl`	Hidden Markov models with stick-breaking priors. IEEE Trans. Signal Process. John W. Paisley, Lawrence Carin
2009	—	`conf`	Non-Parametric Bayesian Dictionary Learning for Sparse Image Representations. NIPS Mingyuan Zhou, Haojun Chen, John W. Paisley, Lu Ren, Guillermo Sapiro, Lawrence Carin
2009	A*	`conf`	Nonparametric factor analysis with beta process priors. ICML John W. Paisley, Lawrence Carin
2008	J	`jnl`	Multi-Task Learning for Analyzing and Sorting Large Databases of Sequential Data. IEEE Trans. Signal Process. Kai Ni, John W. Paisley, Lawrence Carin, David B. Dunson