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ORCIDJohn W. Paisley
John William Paisley
Person information
- affiliation: Columbia University, Department of Electrical Engineering, New York, NY, USA
- affiliation: Columbia University, Data Science Institute, New York, NY, USA
- affiliation (former): University of California Berkeley, Department of Electrical Engineering and Computer Science, CA, USA
- affiliation (former): Princeton University, Computer Science Department, NJ, USA
- affiliation (PhD): Duke University, Durham, NC, USA
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2020 – today
- 2024
[c51]Jian Xu, Delu Zeng, John W. Paisley:
Sparse Inducing Points in Deep Gaussian Processes: Enhancing Modeling with Denoising Diffusion Variational Inference. ICML 2024- [i44]Wei Chen, Shian Du, Shigui Li, Delu Zeng, John W. Paisley:
Entropy-Informed Weighting Channel Normalizing Flow. CoRR abs/2407.04958 (2024) - [i43]Jian Xu, Delu Zeng, John W. Paisley:
Sparse Inducing Points in Deep Gaussian Processes: Enhancing Modeling with Denoising Diffusion Variational Inference. CoRR abs/2407.17033 (2024) - [i42]Jian Xu, Zhiqi Lin, Shigui Li, Min Chen, Junmei Yang, Delu Zeng, John W. Paisley:
Flexible Bayesian Last Layer Models Using Implicit Priors and Diffusion Posterior Sampling. CoRR abs/2408.03746 (2024) - [i41]Jian Xu, Zhiqi Lin, Min Chen, Junmei Yang, Delu Zeng, John W. Paisley:
Fully Bayesian Differential Gaussian Processes through Stochastic Differential Equations. CoRR abs/2408.06069 (2024) - [i40]Jian Xu, Delu Zeng, John W. Paisley:
Information Geometry and Beta Link for Optimizing Sparse Variational Student-t Processes. CoRR abs/2408.06699 (2024) - 2023
- [j32]Manni Liu, Jiabin Huang, Delu Zeng
, Xinghao Ding, John W. Paisley:
A Multiscale Approach to Deep Blind Image Quality Assessment. IEEE Trans. Image Process. 32: 1656-1667 (2023) - [j31]Huangxing Lin, Weihong Zeng, Yihong Zhuang, Xinghao Ding, Yue Huang, John W. Paisley:
Learning Rate Dropout. IEEE Trans. Neural Networks Learn. Syst. 34(11): 9029-9039 (2023) - [c50]Huangxing Lin, Yihong Zhuang, Xinghao Ding, Delu Zeng, Yue Huang, Xiaotong Tu, John W. Paisley:
Self-Supervised Image Denoising Using Implicit Deep Denoiser Prior. AAAI 2023: 1586-1594 - [i39]San Gultekin, Brendan Kitts, Aaron Flores, John W. Paisley:
Nonlinear Kalman Filtering with Reparametrization Gradients. CoRR abs/2303.04450 (2023) - [i38]Jian Xu, Shian Du, Junmei Yang, Xinghao Ding, John W. Paisley, Delu Zeng:
Double Normalizing Flows: Flexible Bayesian Gaussian Process ODEs Learning. CoRR abs/2309.09222 (2023) - 2022
- [j30]Liyan Sun, Chenxin Li, Xinghao Ding, Yue Huang, Zhong Chen, Guisheng Wang, Yizhou Yu, John W. Paisley:
Few-shot medical image segmentation using a global correlation network with discriminative embedding. Comput. Biol. Medicine 140: 105067 (2022) - [c49]Ghazal Fazelnia, John W. Paisley:
Probabilistic Orthogonal Matching Pursuit. IEEE Big Data 2022: 26-35 - [c48]John W. Paisley, Sebastian Rowland, Jeremiah Zhe Liu, Brent A. Coull, Marianthi-Anna Kioumourtzoglou:
Bayesian Nonparametric Model Averaging Using Scalable Gaussian Process Representations. IEEE Big Data 2022: 55-64 - 2021
- [j29]Xueyang Fu, Qi Qi, Zheng-Jun Zha, Xinghao Ding, Feng Wu, John W. Paisley:
Successive Graph Convolutional Network for Image De-raining. Int. J. Comput. Vis. 129(5): 1691-1711 (2021) - [j28]Xueyang Fu, Wu Wang, Yue Huang, Xinghao Ding, John W. Paisley:
Deep Multiscale Detail Networks for Multiband Spectral Image Sharpening. IEEE Trans. Neural Networks Learn. Syst. 32(5): 2090-2104 (2021) - [i37]Huangxing Lin, Yihong Zhuang, Delu Zeng, Yue Huang, Xinghao Ding, John W. Paisley:
Self-Verification in Image Denoising. CoRR abs/2111.00666 (2021) - 2020
- [j27]Liyan Sun, Yawen Wu, Binglin Shu, Xinghao Ding, Congbo Cai, Yue Huang, John W. Paisley:
A dual-domain deep lattice network for rapid MRI reconstruction. Neurocomputing 397: 94-107 (2020) - [j26]Huangxing Lin, Yanlong Li, Xueyang Fu, Xinghao Ding, Yue Huang, John W. Paisley:
Rain O'er Me: Synthesizing Real Rain to Derain With Data Distillation. IEEE Trans. Image Process. 29: 7668-7680 (2020) - [j25]Liyan Sun, Jiexiang Wang, Yue Huang, Xinghao Ding, Hayit Greenspan, John W. Paisley:
An Adversarial Learning Approach to Medical Image Synthesis for Lesion Detection. IEEE J. Biomed. Health Informatics 24(8): 2303-2314 (2020) - [j24]Liyan Sun, Wenao Ma, Xinghao Ding, Yue Huang, Dong Liang, John W. Paisley:
A 3D Spatially Weighted Network for Segmentation of Brain Tissue From MRI. IEEE Trans. Medical Imaging 39(4): 898-909 (2020) - [j23]Xueyang Fu, Borong Liang, Yue Huang, Xinghao Ding, John W. Paisley:
Lightweight Pyramid Networks for Image Deraining. IEEE Trans. Neural Networks Learn. Syst. 31(6): 1794-1807 (2020) - [j22]San Gultekin, Avishek Saha, Adwait Ratnaparkhi, John W. Paisley:
MBA: Mini-Batch AUC Optimization. IEEE Trans. Neural Networks Learn. Syst. 31(12): 5561-5574 (2020) - [c47]Ghazal Fazelnia, Mark Ibrahim, Ceena Modarres, Kevin Wu, John W. Paisley:
Mixed membership recurrent neural networks for modeling customer purchases. ICAIF 2020: 36:1-36:8 - [c46]San Gultekin, John W. Paisley:
Risk Bounds for Low Cost Bipartite Ranking. UAI 2020: 959-968 - [i36]Arunesh Mittal, Paul Sajda, John W. Paisley:
Deep Bayesian Nonparametric Factor Analysis. CoRR abs/2011.04770 (2020) - [i35]Arunesh Mittal, Scott W. Linderman, John W. Paisley, Paul Sajda:
Bayesian recurrent state space model for rs-fMRI. CoRR abs/2011.07365 (2020) - [i34]Huangxing Lin, Yihong Zhuang, Yue Huang, Xinghao Ding, Yizhou Yu, Xiaoqing Liu, John W. Paisley:
Adaptive noise imitation for image denoising. CoRR abs/2011.14512 (2020)
2010 – 2019
- 2019
- [j21]Liyan Sun, Zhiwen Fan, Xueyang Fu, Yue Huang, Xinghao Ding, John William Paisley:
A Deep Information Sharing Network for Multi-Contrast Compressed Sensing MRI Reconstruction. IEEE Trans. Image Process. 28(12): 6141-6153 (2019) - [j20]San Gultekin, John W. Paisley:
Online Forecasting Matrix Factorization. IEEE Trans. Signal Process. 67(5): 1223-1236 (2019) - [c45]Mark Ibrahim, Melissa Louie, Ceena Modarres, John W. Paisley:
Global Explanations of Neural Networks: Mapping the Landscape of Predictions. AIES 2019: 279-287 - [c44]Aonan Zhang, Quan Wang, Zhenyao Zhu, John W. Paisley, Chong Wang:
Fully Supervised Speaker Diarization. ICASSP 2019: 6301-6305 - [c43]Xueyang Fu, Zheng-Jun Zha, Feng Wu, Xinghao Ding, John W. Paisley:
JPEG Artifacts Reduction via Deep Convolutional Sparse Coding. ICCV 2019: 2501-2510 - [c42]Wu Wang, Weihong Zeng, Yue Huang, Xinghao Ding, John W. Paisley:
Deep Blind Hyperspectral Image Fusion. ICCV 2019: 4149-4158 - [c41]Aonan Zhang, John W. Paisley:
Random Function Priors for Correlation Modeling. ICML 2019: 7424-7433 - [c40]Liyan Sun, Zhiwen Fan, Xinghao Ding, Yue Huang, John W. Paisley:
Joint CS-MRI Reconstruction and Segmentation with a Unified Deep Network. IPMI 2019: 492-504 - [c39]Tao Tu, John W. Paisley, Stefan Haufe, Paul Sajda:
A state-space model for inferring effective connectivity of latent neural dynamics from simultaneous EEG/fMRI. NeurIPS 2019: 4664-4673 - [c38]Jeremiah Z. Liu, John W. Paisley, Marianthi-Anna Kioumourtzoglou, Brent A. Coull:
Accurate Uncertainty Estimation and Decomposition in Ensemble Learning. NeurIPS 2019: 8950-8961 - [i33]Mark Ibrahim, Melissa Louie, Ceena Modarres, John W. Paisley:
Global Explanations of Neural Networks: Mapping the Landscape of Predictions. CoRR abs/1902.02384 (2019) - [i32]Huangxing Lin, Yanlong Li, Xinghao Ding, Weihong Zeng, Yue Huang, John W. Paisley:
Rain O'er Me: Synthesizing real rain to derain with data distillation. CoRR abs/1904.04605 (2019) - [i31]Aonan Zhang, John W. Paisley:
Random Function Priors for Correlation Modeling. CoRR abs/1905.03826 (2019) - [i30]Adji B. Dieng, John W. Paisley:
Reweighted Expectation Maximization. CoRR abs/1906.05850 (2019) - [i29]Jeremiah Zhe Liu, John W. Paisley, Marianthi-Anna Kioumourtzoglou, Brent A. Coull:
Accurate Uncertainty Estimation and Decomposition in Ensemble Learning. CoRR abs/1911.04061 (2019) - [i28]Huangxing Lin, Weihong Zeng, Xinghao Ding, Yue Huang, Chenxi Huang, John W. Paisley:
Learning Rate Dropout. CoRR abs/1912.00144 (2019) - [i27]San Gultekin, John W. Paisley:
Risk Bounds for Low Cost Bipartite Ranking. CoRR abs/1912.00537 (2019) - [i26]Huangxing Lin, Weihong Zeng, Xinghao Ding, Xueyang Fu, Yue Huang, John W. Paisley:
Noise2Blur: Online Noise Extraction and Denoising. CoRR abs/1912.01158 (2019) - 2018
- [j19]Lei Liu, Feng Zhou, Xueru Bai, John W. Paisley, Hongbing Ji:
A Modified EM Algorithm for ISAR Scatterer Trajectory Matrix Completion. IEEE Trans. Geosci. Remote. Sens. 56(7): 3953-3962 (2018) - [j18]Xiangyong Cao, Feng Zhou, Lin Xu, Deyu Meng, Zongben Xu, John W. Paisley:
Hyperspectral Image Classification With Markov Random Fields and a Convolutional Neural Network. IEEE Trans. Image Process. 27(5): 2354-2367 (2018) - [c37]Liyan Sun, Zhiwen Fan, Yue Huang, Xinghao Ding, John W. Paisley:
Compressed Sensing MRI Using a Recursive Dilated Network. AAAI 2018: 2444-2451 - [c36]Zhiwen Fan, Liyan Sun, Xinghao Ding, Yue Huang, Congbo Cai, John W. Paisley:
A Segmentation-Aware Deep Fusion Network for Compressed Sensing MRI. ECCV (6) 2018: 55-70 - [c35]San Gultekin, Aonan Zhang, John W. Paisley:
Asymptotic Simulated Annealing for Variational Inference. GLOBECOM 2018: 1-7 - [c34]Ghazal Fazelnia, John W. Paisley:
CRVI: Convex Relaxation for Variational Inference. ICML 2018: 1476-1484 - [c33]Aonan Zhang, John W. Paisley:
Deep Bayesian Nonparametric Tracking. ICML 2018: 5828-5836 - [c32]Shulian Cai, Jiabin Huang, Delu Zeng, Xinghao Ding, John W. Paisley:
MEnet: A Metric Expression Network for Salient Object Segmentation. IJCAI 2018: 598-605 - [i25]Liyan Sun, Zhiwen Fan, Yue Huang, Xinghao Ding, John W. Paisley:
A Deep Error Correction Network for Compressed Sensing MRI. CoRR abs/1803.08763 (2018) - [i24]Liyan Sun, Zhiwen Fan, Xinghao Ding, Congbo Cai, Yue Huang, John W. Paisley:
A Divide-and-Conquer Approach to Compressed Sensing MRI. CoRR abs/1803.09909 (2018) - [i23]Zhiwen Fan, Liyan Sun, Xinghao Ding, Yue Huang, Congbo Cai, John W. Paisley:
A Segmentation-aware Deep Fusion Network for Compressed Sensing MRI. CoRR abs/1804.01210 (2018) - [i22]Liyan Sun, Zhiwen Fan, Yue Huang, Xinghao Ding, John W. Paisley:
A Deep Information Sharing Network for Multi-contrast Compressed Sensing MRI Reconstruction. CoRR abs/1804.03596 (2018) - [i21]Liyan Sun, Zhiwen Fan, Yue Huang, Xinghao Ding, John W. Paisley:
Joint CS-MRI Reconstruction and Segmentation with a Unified Deep Network. CoRR abs/1805.02165 (2018) - [i20]Shulian Cai, Jiabin Huang, Delu Zeng, Xinghao Ding, John W. Paisley:
MEnet: A Metric Expression Network for Salient Object Segmentation. CoRR abs/1805.05638 (2018) - [i19]Xueyang Fu, Borong Liang, Yue Huang, Xinghao Ding, John W. Paisley:
Lightweight Pyramid Networks for Image Deraining. CoRR abs/1805.06173 (2018) - [i18]San Gultekin, Avishek Saha, Adwait Ratnaparkhi, John W. Paisley:
MBA: Mini-Batch AUC Optimization. CoRR abs/1805.11221 (2018) - [i17]Aonan Zhang, Quan Wang, Zhenyao Zhu, John W. Paisley, Chong Wang:
Fully Supervised Speaker Diarization. CoRR abs/1810.04719 (2018) - [i16]Liyan Sun, Jiexiang Wang, Xinghao Ding, Yue Huang, John W. Paisley:
An Adversarial Learning Approach to Medical Image Synthesis for Lesion Removal. CoRR abs/1810.10850 (2018) - [i15]Ceena Modarres, Mark Ibrahim, Melissa Louie, John W. Paisley:
Towards Explainable Deep Learning for Credit Lending: A Case Study. CoRR abs/1811.06471 (2018) - [i14]Xueyang Fu, Qi Qi, Yue Huang, Xinghao Ding, Feng Wu, John W. Paisley:
A Deep Tree-Structured Fusion Model for Single Image Deraining. CoRR abs/1811.08632 (2018) - [i13]Jeremiah Zhe Liu, John W. Paisley, Marianthi-Anna Kioumourtzoglou, Brent A. Coull:
Adaptive and Calibrated Ensemble Learning with Dependent Tail-free Process. CoRR abs/1812.03350 (2018) - [i12]Ghazal Fazelnia, Mark Ibrahim, Ceena Modarres, Kevin Wu, John W. Paisley:
Mixed Membership Recurrent Neural Networks. CoRR abs/1812.09645 (2018) - 2017
- [j17]Vicky Chen, John W. Paisley, Xinghua Lu:
Revealing common disease mechanisms shared by tumors of different tissues of origin through semantic representation of genomic alterations and topic modeling. BMC Genom. 18(S2) (2017) - [j16]Xueyang Fu, Jiabin Huang, Xinghao Ding, Yinghao Liao, John W. Paisley:
Clearing the Skies: A Deep Network Architecture for Single-Image Rain Removal. IEEE Trans. Image Process. 26(6): 2944-2956 (2017) - [j15]San Gultekin, John W. Paisley:
Nonlinear Kalman Filtering With Divergence Minimization. IEEE Trans. Signal Process. 65(23): 6319-6331 (2017) - [c31]Xueyang Fu, Jiabin Huang, Delu Zeng, Yue Huang, Xinghao Ding, John W. Paisley:
Removing Rain from Single Images via a Deep Detail Network. CVPR 2017: 1715-1723 - [c30]Junfeng Yang, Xueyang Fu, Yuwen Hu, Yue Huang, Xinghao Ding, John W. Paisley:
PanNet: A Deep Network Architecture for Pan-Sharpening. ICCV 2017: 1753-1761 - [c29]Adji B. Dieng, Chong Wang, Jianfeng Gao, John W. Paisley:
TopicRNN: A Recurrent Neural Network with Long-Range Semantic Dependency. ICLR (Poster) 2017 - [c28]Shiliang Sun, John W. Paisley, Qiuyang Liu:
Location Dependent Dirichlet Processes. IScIDE 2017: 64-76 - [c27]Adji Bousso Dieng, Dustin Tran, Rajesh Ranganath, John W. Paisley, David M. Blei:
Variational Inference via \chi Upper Bound Minimization. NIPS 2017: 2732-2741 - [i11]Xiangyong Cao, Feng Zhou, Lin Xu, Deyu Meng, Zongben Xu, John W. Paisley:
Hyperspectral Image Segmentation with Markov Random Fields and a Convolutional Neural Network. CoRR abs/1705.00727 (2017) - [i10]Shiliang Sun, John W. Paisley, Qiuyang Liu:
Location Dependent Dirichlet Processes. CoRR abs/1707.00260 (2017) - [i9]San Gultekin, John W. Paisley:
Online Forecasting Matrix Factorization. CoRR abs/1712.08734 (2017) - 2016
- [j14]Xueyang Fu, Delu Zeng, Yue Huang, Yinghao Liao, Xinghao Ding, John W. Paisley:
A fusion-based enhancing method for weakly illuminated images. Signal Process. 129: 82-96 (2016) - [c26]Aonan Zhang, San Gultekin, John W. Paisley:
Stochastic Variational Inference for the HDP-HMM. AISTATS 2016: 800-808 - [c25]Aonan Zhang, John W. Paisley:
Markov Latent Feature Models. ICML 2016: 1129-1137 - [i8]Xueyang Fu, Jiabin Huang, Xinghao Ding, Yinghao Liao, John W. Paisley:
Clearing the Skies: A deep network architecture for single-image rain removal. CoRR abs/1609.02087 (2016) - [i7]Adji B. Dieng, Dustin Tran, Rajesh Ranganath, John W. Paisley, David M. Blei:
The $χ$-Divergence for Approximate Inference. CoRR abs/1611.00328 (2016) - [i6]Adji B. Dieng, Chong Wang, Jianfeng Gao, John W. Paisley:
TopicRNN: A Recurrent Neural Network with Long-Range Semantic Dependency. CoRR abs/1611.01702 (2016) - 2015
- [j13]John W. Paisley, Chong Wang, David M. Blei, Michael I. Jordan:
Nested Hierarchical Dirichlet Processes. IEEE Trans. Pattern Anal. Mach. Intell. 37(2): 256-270 (2015) - [j12]Tamara Broderick, Lester W. Mackey, John W. Paisley, Michael I. Jordan:
Combinatorial Clustering and the Beta Negative Binomial Process. IEEE Trans. Pattern Anal. Mach. Intell. 37(2): 290-306 (2015) - [c24]Sarper Sertoglu, John W. Paisley:
Scalable Bayesian nonparametric dictionary learning. EUSIPCO 2015: 2771-2775 - [c23]Yiyong Jiang, Xinghao Ding, Delu Zeng, Yue Huang, John W. Paisley:
Pan-Sharpening with a Hyper-Laplacian Penalty. ICCV 2015: 540-548 - [c22]Dawen Liang, John W. Paisley:
Landmarking Manifolds with Gaussian Processes. ICML 2015: 466-474 - [c21]Aonan Zhang, John W. Paisley:
Markov Mixed Membership Models. ICML 2015: 475-483 - [c20]Aaron Schein, John W. Paisley, David M. Blei, Hanna M. Wallach:
Bayesian Poisson Tensor Factorization for Inferring Multilateral Relations from Sparse Dyadic Event Counts. KDD 2015: 1045-1054 - [i5]San Gultekin, John W. Paisley:
A Collaborative Kalman Filter for Time-Evolving Dyadic Processes. CoRR abs/1501.05624 (2015) - [i4]Aaron Schein, John W. Paisley, David M. Blei, Hanna M. Wallach:
Bayesian Poisson Tensor Factorization for Inferring Multilateral Relations from Sparse Dyadic Event Counts. CoRR abs/1506.03493 (2015) - 2014
- [j11]Yue Huang, John W. Paisley, Qin Lin, Xinghao Ding, Xueyang Fu, Xiao-Ping (Steven) Zhang:
Bayesian Nonparametric Dictionary Learning for Compressed Sensing MRI. IEEE Trans. Image Process. 23(12): 5007-5019 (2014) - [c19]Xinghao Ding, Yiyong Jiang, Yue Huang, John W. Paisley:
Pan-sharpening with a Bayesian nonparametric dictionary learning model. AISTATS 2014: 176-184 - [c18]San Gultekin, John W. Paisley:
A Collaborative Kalman Filter for Time-Evolving Dyadic Processes. ICDM 2014: 140-149 - [c17]Dawen Liang, John W. Paisley, Dan Ellis:
Codebook-based Scalable Music Tagging with Poisson Matrix Factorization. ISMIR 2014: 167-172 - [r1]John W. Paisley, David M. Blei, Michael I. Jordan:
Bayesian Nonnegative Matrix Factorization with Stochastic Variational Inference. Handbook of Mixed Membership Models and Their Applications 2014: 205-224 - 2013
- [j10]Matthew D. Hoffman, David M. Blei, Chong Wang, John W. Paisley:
Stochastic variational inference. J. Mach. Learn. Res. 14(1): 1303-1347 (2013) - [c16]Jin Xie, Yue Huang, John W. Paisley, Xinghao Ding, Xiao-Ping (Steven) Zhang:
Pan-sharpening based on nonparametric Bayesian adaptive dictionary learning. ICIP 2013: 2039-2042 - [c15]Xinghao Ding, John W. Paisley, Yue Huang, Xianbo Chen, Feng Huang, Xiao-Ping (Steven) Zhang:
Compressed sensing MRI with Bayesian dictionary learning. ICIP 2013: 2319-2323 - [c14]John W. Paisley, Chong Wang, David M. Blei, Michael I. Jordan:
A Nested HDP for Hierarchical Topic Models. ICLR (Workshop) 2013 - [i3]Yue Huang, John W. Paisley, Xianbo Chen, Xinghao Ding, Feng Huang, Xiao-Ping (Steven) Zhang:
MR Image Reconstruction from Undersampled k-Space with Bayesian Dictionary Learning. CoRR abs/1302.2712 (2013) - 2012
- [j9]Mingyuan Zhou, Haojun Chen, John W. Paisley, Lu Ren, Lingbo Li, Zhengming Xing, David B. Dunson, Guillermo Sapiro, Lawrence Carin:
Nonparametric Bayesian Dictionary Learning for Analysis of Noisy and Incomplete Images. IEEE Trans. Image Process. 21(1): 130-144 (2012) - [c13]John W. Paisley, David M. Blei, Michael I. Jordan:
Variational Bayesian Inference with Stochastic Search. ICML 2012 - [c12]John W. Paisley, David M. Blei, Michael I. Jordan:
Stick-Breaking Beta Processes and the Poisson Process. AISTATS 2012: 850-858 - [i2]Matthew D. Hoffman, David M. Blei, Chong Wang, John W. Paisley:
Stochastic Variational Inference. CoRR abs/1206.7051 (2012) - [i1]John W. Paisley, Chong Wang, David M. Blei, Michael I. Jordan:
Nested Hierarchical Dirichlet Processes. CoRR abs/1210.6738 (2012) - 2011
- [j8]Minhua Chen, Jorge G. Silva, John W. Paisley, Chunping Wang, David B. Dunson, Lawrence Carin:
Corrections to "Compressive Sensing on Manifolds Using a Nonparametric Mixture of Factor Analyzers: Algorithm and Performance Bounds". IEEE Trans. Signal Process. 59(3): 1329 (2011) - [c11]John W. Paisley, Lawrence Carin, David M. Blei:
Variational Inference for Stick-Breaking Beta Process Priors. ICML 2011: 889-896 - [c10]John W. Paisley, Chong Wang, David M. Blei:
The Discrete Infinite Logistic Normal Distribution for Mixed-Membership Modeling. AISTATS 2011: 74-82 - [c9]Chong Wang, John W. Paisley, David M. Blei:
Online Variational Inference for the Hierarchical Dirichlet Process. AISTATS 2011: 752-760 - 2010
- [b1]John William Paisley:
Machine Learning with Dirichlet and Beta Process Priors: Theory and Applications. Duke University, Durham, NC, USA, 2010 - [j7]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:
Bayesian Inference of the Number of Factors in Gene-Expression Analysis: Application to Human Virus Challenge Studies. BMC Bioinform. 11: 552 (2010) - [j6]Iulian Pruteanu-Malinici, Lu Ren, John W. Paisley, Eric Wang, Lawrence Carin:
Hierarchical Bayesian Modeling of Topics in Time-Stamped Documents. IEEE Trans. Pattern Anal. Mach. Intell. 32(6): 996-1011 (2010) - [j5]John W. Paisley, Xuejun Liao, Lawrence Carin:
Active learning and basis selection for kernel-based linear models: a Bayesian perspective. IEEE Trans. Signal Process. 58(5): 2686-2700 (2010) - [j4]Minhua Chen, Jorge G. Silva, John W. Paisley, Chunping Wang, David B. Dunson, Lawrence Carin:
Compressive Sensing on Manifolds Using a Nonparametric Mixture of Factor Analyzers: Algorithm and Performance Bounds. IEEE Trans. Signal Process. 58(12): 6140-6155 (2010) - [c8]Bo Chen, John W. Paisley, Lawrence Carin:
Sparse linear regression with beta process priors. ICASSP 2010: 1234-1237 - [c7]John W. Paisley, Lawrence Carin:
A nonparametric Bayesian model for kernel matrix completion. ICASSP 2010: 2090-2093 - [c6]John W. Paisley, Mingyuan Zhou, Guillermo Sapiro, Lawrence Carin:
Nonparametric image interpolation and dictionary learning using spatially-dependent Dirichlet and beta process priors. ICIP 2010: 1869-1872 - [c5]John W. Paisley, Aimee K. Zaas, Christopher W. Woods, Geoffrey S. Ginsburg, Lawrence Carin:
A Stick-Breaking Construction of the Beta Process. ICML 2010: 847-854
2000 – 2009
- 2009
- [j3]John W. Paisley, Lawrence Carin:
Hidden Markov models with stick-breaking priors. IEEE Trans. Signal Process. 57(10): 3905-3917 (2009) - [c4]John W. Paisley, Lawrence Carin:
Dirichlet process mixture models with multiple modalities. ICASSP 2009: 1613-1616 - [c3]John W. Paisley, Lawrence Carin:
Nonparametric factor analysis with beta process priors. ICML 2009: 777-784 - [c2]Mingyuan Zhou, Haojun Chen, John W. Paisley, Lu Ren, Guillermo Sapiro, Lawrence Carin:
Non-Parametric Bayesian Dictionary Learning for Sparse Image Representations. NIPS 2009: 2295-2303 - 2008
- [j2]Kai Ni, John W. Paisley, Lawrence Carin, David B. Dunson:
Multi-Task Learning for Analyzing and Sorting Large Databases of Sequential Data. IEEE Trans. Signal Process. 56(8-2): 3918-3931 (2008) - 2007
- [j1]Yuting Qi, John William Paisley, Lawrence Carin:
Music Analysis Using Hidden Markov Mixture Models. IEEE Trans. Signal Process. 55(11): 5209-5224 (2007) - [c1]Yuting Qi, John William Paisley, Lawrence Carin:
Dirichlet Process HMM Mixture Models with Application to Music Analysis. ICASSP (2) 2007: 465-468
Coauthor Index
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last updated on 2024-11-07 21:29 CET by the dblp team
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