John W. Paisley

Publication Activity (10 Years)

Years Active: 2008-2024
Publications (10 Years): 80

Top Venues

CoRR

ICML

IEEE Trans. Image Process.

IEEE Trans. Neural Networks Learn. Syst.

Publications

Jian Xu, Delu Zeng, John W. Paisley
Sparse Inducing Points in Deep Gaussian Processes: Enhancing Modeling with Denoising Diffusion Variational Inference. CoRR (2024)
Wei Chen, Shian Du, Shigui Li, Delu Zeng, John W. Paisley
Entropy-Informed Weighting Channel Normalizing Flow. CoRR (2024)
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 (2023)
San Gultekin, Brendan Kitts, Aaron Flores, John W. Paisley
Nonlinear Kalman Filtering with Reparametrization Gradients. CoRR (2023)
Huangxing Lin, Weihong Zeng, Yihong Zhuang, Xinghao Ding, Yue Huang, John W. Paisley
Learning Rate Dropout. IEEE Trans. Neural Networks Learn. Syst. 34 (11) (2023)
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)
Jian Xu, Shian Du, Junmei Yang, Xinghao Ding, John W. Paisley, Delu Zeng
Double Normalizing Flows: Flexible Bayesian Gaussian Process ODEs Learning. CoRR (2023)
Ghazal Fazelnia, John W. Paisley
Probabilistic Orthogonal Matching Pursuit. Big Data (2022)
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 (2022)
John W. Paisley, Sebastian Rowland, Jeremiah Zhe Liu, Brent A. Coull, Marianthi-Anna Kioumourtzoglou
Bayesian Nonparametric Model Averaging Using Scalable Gaussian Process Representations. Big Data (2022)
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) (2021)
Huangxing Lin, Yihong Zhuang, Delu Zeng, Yue Huang, Xinghao Ding, John W. Paisley
Self-Verification in Image Denoising. CoRR (2021)
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) (2021)
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) (2020)
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) (2020)
San Gultekin, Avishek Saha, Adwait Ratnaparkhi, John W. Paisley
MBA: Mini-Batch AUC Optimization. IEEE Trans. Neural Networks Learn. Syst. 31 (12) (2020)
Arunesh Mittal, Scott W. Linderman, John W. Paisley, Paul Sajda
Bayesian recurrent state space model for rs-fMRI. CoRR (2020)
San Gultekin, John W. Paisley
Risk Bounds for Low Cost Bipartite Ranking. UAI (2020)
Arunesh Mittal, Paul Sajda, John W. Paisley
Deep Bayesian Nonparametric Factor Analysis. CoRR (2020)
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 (2020)
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) (2020)
Huangxing Lin, Yihong Zhuang, Yue Huang, Xinghao Ding, Yizhou Yu, Xiaoqing Liu, John W. Paisley
Adaptive noise imitation for image denoising. CoRR (2020)
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 (2020)
Ghazal Fazelnia, Mark Ibrahim, Ceena Modarres, Kevin Wu, John W. Paisley
Mixed membership recurrent neural networks for modeling customer purchases. ICAIF (2020)
Jeremiah Zhe Liu, John W. Paisley, Marianthi-Anna Kioumourtzoglou, Brent A. Coull
Accurate Uncertainty Estimation and Decomposition in Ensemble Learning. CoRR (2019)
Aonan Zhang, John W. Paisley
Random Function Priors for Correlation Modeling. CoRR (2019)
Aonan Zhang, Quan Wang, Zhenyao Zhu, John W. Paisley, Chong Wang
Fully Supervised Speaker Diarization. ICASSP (2019)
Huangxing Lin, Weihong Zeng, Xinghao Ding, Xueyang Fu, Yue Huang, John W. Paisley
Noise2Blur: Online Noise Extraction and Denoising. CoRR (2019)
Wu Wang, Weihong Zeng, Yue Huang, Xinghao Ding, John W. Paisley
Deep Blind Hyperspectral Image Fusion. ICCV (2019)
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)
Xueyang Fu, Zheng-Jun Zha, Feng Wu, Xinghao Ding, John W. Paisley
JPEG Artifacts Reduction via Deep Convolutional Sparse Coding. ICCV (2019)
San Gultekin, John W. Paisley
Risk Bounds for Low Cost Bipartite Ranking. CoRR (2019)
Jeremiah Z. Liu, John W. Paisley, Marianthi-Anna Kioumourtzoglou, Brent A. Coull
Accurate Uncertainty Estimation and Decomposition in Ensemble Learning. NeurIPS (2019)
Mark Ibrahim, Melissa Louie, Ceena Modarres, John W. Paisley
Global Explanations of Neural Networks: Mapping the Landscape of Predictions. CoRR (2019)
Adji B. Dieng, John W. Paisley
Reweighted Expectation Maximization. CoRR (2019)
Mark Ibrahim, Melissa Louie, Ceena Modarres, John W. Paisley
Global Explanations of Neural Networks: Mapping the Landscape of Predictions. AIES (2019)
Liyan Sun, Zhiwen Fan, Xinghao Ding, Yue Huang, John W. Paisley
Joint CS-MRI Reconstruction and Segmentation with a Unified Deep Network. IPMI (2019)
San Gultekin, John W. Paisley
Online Forecasting Matrix Factorization. IEEE Trans. Signal Process. 67 (5) (2019)
Aonan Zhang, John W. Paisley
Random Function Priors for Correlation Modeling. ICML (2019)
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 (2019)
Huangxing Lin, Weihong Zeng, Xinghao Ding, Yue Huang, Chenxi Huang, John W. Paisley
Learning Rate Dropout. CoRR (2019)
Liyan Sun, Zhiwen Fan, Yue Huang, Xinghao Ding, John W. Paisley
Joint CS-MRI Reconstruction and Segmentation with a Unified Deep Network. CoRR (2018)
Aonan Zhang, Quan Wang, Zhenyao Zhu, John W. Paisley, Chong Wang
Fully Supervised Speaker Diarization. CoRR (2018)
San Gultekin, Aonan Zhang, John W. Paisley
Asymptotic Simulated Annealing for Variational Inference. GLOBECOM (2018)
Xueyang Fu, Qi Qi, Yue Huang, Xinghao Ding, Feng Wu, John W. Paisley
A Deep Tree-Structured Fusion Model for Single Image Deraining. CoRR (2018)
Liyan Sun, Zhiwen Fan, Yue Huang, Xinghao Ding, John W. Paisley
A Deep Information Sharing Network for Multi-contrast Compressed Sensing MRI Reconstruction. CoRR (2018)
Zhiwen Fan, Liyan Sun, Xinghao Ding, Yue Huang, Congbo Cai, John W. Paisley
A Segmentation-aware Deep Fusion Network for Compressed Sensing MRI. CoRR (2018)
Liyan Sun, Jiexiang Wang, Xinghao Ding, Yue Huang, John W. Paisley
An Adversarial Learning Approach to Medical Image Synthesis for Lesion Removal. CoRR (2018)
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) (2018)
Ghazal Fazelnia, John W. Paisley
CRVI: Convex Relaxation for Variational Inference. ICML (2018)
Liyan Sun, Zhiwen Fan, Yue Huang, Xinghao Ding, John W. Paisley
A Deep Error Correction Network for Compressed Sensing MRI. CoRR (2018)
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)
Shulian Cai, Jiabin Huang, Delu Zeng, Xinghao Ding, John W. Paisley
MEnet: A Metric Expression Network for Salient Object Segmentation. IJCAI (2018)
Ceena Modarres, Mark Ibrahim, Melissa Louie, John W. Paisley
Towards Explainable Deep Learning for Credit Lending: A Case Study. CoRR (2018)
Liyan Sun, Zhiwen Fan, Yue Huang, Xinghao Ding, John W. Paisley
Compressed Sensing MRI Using a Recursive Dilated Network. AAAI (2018)
San Gultekin, Avishek Saha, Adwait Ratnaparkhi, John W. Paisley
MBA: Mini-Batch AUC Optimization. CoRR (2018)
Shulian Cai, Jiabin Huang, Delu Zeng, Xinghao Ding, John W. Paisley
MEnet: A Metric Expression Network for Salient Object Segmentation. CoRR (2018)
Ghazal Fazelnia, Mark Ibrahim, Ceena Modarres, Kevin Wu, John W. Paisley
Mixed Membership Recurrent Neural Networks. CoRR (2018)
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) (2018)
Aonan Zhang, John W. Paisley
Deep Bayesian Nonparametric Tracking. ICML (2018)
Xueyang Fu, Borong Liang, Yue Huang, Xinghao Ding, John W. Paisley
Lightweight Pyramid Networks for Image Deraining. CoRR (2018)
Jeremiah Zhe Liu, John W. Paisley, Marianthi-Anna Kioumourtzoglou, Brent A. Coull
Adaptive and Calibrated Ensemble Learning with Dependent Tail-free Process. CoRR (2018)
Liyan Sun, Zhiwen Fan, Xinghao Ding, Congbo Cai, Yue Huang, John W. Paisley
A Divide-and-Conquer Approach to Compressed Sensing MRI. CoRR (2018)
Shiliang Sun, John W. Paisley, Qiuyang Liu
Location Dependent Dirichlet Processes. CoRR (2017)
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) (2017)
Adji B. Dieng, Chong Wang, Jianfeng Gao, John W. Paisley
TopicRNN: A Recurrent Neural Network with Long-Range Semantic Dependency. ICLR (Poster) (2017)
Junfeng Yang, Xueyang Fu, Yuwen Hu, Yue Huang, Xinghao Ding, John W. Paisley
PanNet: A Deep Network Architecture for Pan-Sharpening. ICCV (2017)
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)
Shiliang Sun, John W. Paisley, Qiuyang Liu
Location Dependent Dirichlet Processes. IScIDE (2017)
Adji Bousso Dieng, Dustin Tran, Rajesh Ranganath, John W. Paisley, David M. Blei
Variational Inference via \chi Upper Bound Minimization. NIPS (2017)
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 (2017)
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)
San Gultekin, John W. Paisley
Online Forecasting Matrix Factorization. CoRR (2017)
San Gultekin, John W. Paisley
Nonlinear Kalman Filtering With Divergence Minimization. IEEE Trans. Signal Process. 65 (23) (2017)
Xueyang Fu, Jiabin Huang, Xinghao Ding, Yinghao Liao, John W. Paisley
Clearing the Skies: A deep network architecture for single-image rain removal. CoRR (2016)
Adji B. Dieng, Dustin Tran, Rajesh Ranganath, John W. Paisley, David M. Blei
The $χ$-Divergence for Approximate Inference. CoRR (2016)
Adji B. Dieng, Chong Wang, Jianfeng Gao, John W. Paisley
TopicRNN: A Recurrent Neural Network with Long-Range Semantic Dependency. CoRR (2016)
Aonan Zhang, San Gultekin, John W. Paisley
Stochastic Variational Inference for the HDP-HMM. AISTATS (2016)
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 (2016)
Aonan Zhang, John W. Paisley
Markov Latent Feature Models. ICML (2016)
Aonan Zhang, John W. Paisley
Markov Mixed Membership Models. ICML (2015)
Dawen Liang, John W. Paisley
Landmarking Manifolds with Gaussian Processes. ICML (2015)
John W. Paisley, Chong Wang, David M. Blei, Michael I. Jordan
Nested Hierarchical Dirichlet Processes. IEEE Trans. Pattern Anal. Mach. Intell. 37 (2) (2015)
San Gultekin, John W. Paisley
A Collaborative Kalman Filter for Time-Evolving Dyadic Processes. CoRR (2015)
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 (2015)
Sarper Sertoglu, John W. Paisley
Scalable Bayesian nonparametric dictionary learning. EUSIPCO (2015)
Yiyong Jiang, Xinghao Ding, Delu Zeng, Yue Huang, John W. Paisley
Pan-Sharpening with a Hyper-Laplacian Penalty. ICCV (2015)
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)
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) (2015)
Xinghao Ding, Yiyong Jiang, Yue Huang, John W. Paisley
Pan-sharpening with a Bayesian nonparametric dictionary learning model. AISTATS (2014)
Dawen Liang, John W. Paisley, Dan Ellis
Codebook-based Scalable Music Tagging with Poisson Matrix Factorization. ISMIR (2014)
San Gultekin, John W. Paisley
A Collaborative Kalman Filter for Time-Evolving Dyadic Processes. ICDM (2014)
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) (2014)
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 (2013)
Matthew D. Hoffman, David M. Blei, Chong Wang, John W. Paisley
Stochastic variational inference. J. Mach. Learn. Res. 14 (1) (2013)
John W. Paisley, Chong Wang, David M. Blei, Michael I. Jordan
A Nested HDP for Hierarchical Topic Models ICLR (Workshop) (2013)
Xinghao Ding, John W. Paisley, Yue Huang, Xianbo Chen, Feng Huang, Xiao-Ping (Steven) Zhang
Compressed sensing MRI with Bayesian dictionary learning. ICIP (2013)
Jin Xie, Yue Huang, John W. Paisley, Xinghao Ding, Xiao-Ping (Steven) Zhang
Pan-sharpening based on nonparametric Bayesian adaptive dictionary learning. ICIP (2013)
John W. Paisley, Chong Wang, David M. Blei, Michael I. Jordan
Nested Hierarchical Dirichlet Processes CoRR (2012)
Matthew D. Hoffman, David M. Blei, Chong Wang, John W. Paisley
Stochastic Variational Inference. CoRR (2012)

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Publication Activity (10 Years)

Top Topics

Top Venues

John W. Paisley