World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
45
Citations
13462
World Ranking
7031
National Ranking
3083

Overview

John Paisley is affiliated with Columbia University in the United States and conducts research primarily in the field of Computer Science. Their work spans several specialized subfields, including Artificial Intelligence, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Health, Toxicology and Mutagenesis, and Cognitive Neuroscience.

Their research focuses on topics such as Gaussian Processes and Bayesian Inference, Image and Signal Denoising Methods, Air Quality Monitoring and Forecasting, Air Quality and Health Impacts, Statistical Methods and Inference, Advanced Image Fusion Techniques, and Image Enhancement Techniques.

Recent publications by John Paisley include the following papers:

  • Deep Multiscale Detail Networks for Multiband Spectral Image Sharpening, 2020, IEEE Transactions on Neural Networks and Learning Systems
  • An Adversarial Learning Approach to Medical Image Synthesis for Lesion Detection, 2020, IEEE Journal of Biomedical and Health Informatics
  • Few-shot medical image segmentation using a global correlation network with discriminative embedding, 2021, Computers in Biology and Medicine
  • Successive Graph Convolutional Network for Image De-raining, 2021, International Journal of Computer Vision
  • A dual-domain deep lattice network for rapid MRI reconstruction, 2020, Neurocomputing

Among frequent collaborators in John Paisley's work are Delu Zeng, Xinghao Ding, Yue Huang, Jian Xu, and Junmei Yang.

John Paisley regularly publishes in several venues, with notable frequency in:

  • arXiv (Cornell University)
  • SSRN Electronic Journal
  • ISEE Conference Abstracts
  • IEEE Transactions on Neural Networks and Learning Systems
  • IEEE Transactions on Image Processing

Best Publications

  • Stochastic variational inference

    Matthew D. Hoffman;David M. Blei;Chong Wang;John Paisley

  • Removing Rain from Single Images via a Deep Detail Network

    Xueyang Fu;Jiabin Huang;Delu Zeng;Yue Huang

  • Clearing the Skies: A Deep Network Architecture for Single-Image Rain Removal

    Xueyang Fu;Jiabin Huang;Xinghao Ding;Yinghao Liao

  • PanNet: A Deep Network Architecture for Pan-Sharpening

    Junfeng Yang;Xueyang Fu;Yuwen Hu;Yue Huang

  • A fusion-based enhancing method for weakly illuminated images

    Xueyang Fu;Delu Zeng;Yue Huang;Yinghao Liao

  • Online variational inference for the hierarchical Dirichlet process

    Chong Wang;John Paisley;David M. Blei

  • Nonparametric Bayesian Dictionary Learning for Analysis of Noisy and Incomplete Images

    Mingyuan Zhou;Haojun Chen;John Paisley;Lu Ren

  • Hyperspectral Image Classification With Markov Random Fields and a Convolutional Neural Network

    Xiangyong Cao;Feng Zhou;Lin Xu;Deyu Meng

  • Variational Bayesian Inference with Stochastic Search

    David M. Blei;Michael I. Jordan;John W. Paisley

  • Lightweight Pyramid Networks for Image Deraining

    Xueyang Fu;Borong Liang;Yue Huang;Xinghao Ding

  • Variational Bayesian Inference with Stochastic Search

    John Paisley;David Blei;Michael Jordan

  • Nonparametric factor analysis with beta process priors

    John Paisley;Lawrence Carin

  • Non-Parametric Bayesian Dictionary Learning for Sparse Image Representations

    Mingyuan Zhou;Haojun Chen;Lu Ren;Guillermo Sapiro

  • Nested Hierarchical Dirichlet Processes

    John Paisley;Chong Wang;David M. Blei;Michael I. Jordan

  • Fully Supervised Speaker Diarization

    Aonan Zhang;Quan Wang;Zhenyao Zhu;John Paisley

  • TopicRNN: A Recurrent Neural Network with Long-Range Semantic Dependency

    Adji B. Dieng;Chong Wang;Jianfeng Gao;John William Paisley

  • Compressive Sensing on Manifolds Using a Nonparametric Mixture of Factor Analyzers: Algorithm and Performance Bounds

    Minhua Chen;J Silva;J Paisley;Chunping Wang

  • Bayesian Nonparametric Dictionary Learning for Compressed Sensing MRI

    Yue Huang;John Paisley;Qin Lin;Xinghao Ding

  • An Adversarial Learning Approach to Medical Image Synthesis for Lesion Detection

    Liyan Sun;Jiexiang Wang;Yue Huang;Xinghao Ding

  • Deep Multiscale Detail Networks for Multiband Spectral Image Sharpening

    Xueyang Fu;Wu Wang;Yue Huang;Xinghao Ding

  • Variational Inference via $\chi$ Upper Bound Minimization

    Adji Bousso Dieng;Dustin Tran;Rajesh Ranganath;John W. Paisley

  • Music Analysis Using Hidden Markov Mixture Models

    Yuting Qi;J.W. Paisley;L. Carin

Frequent Co-Authors

Xinghao Ding
Xinghao Ding Xiamen University
Yue Huang
Yue Huang Xiamen University
Lawrence Carin
Lawrence Carin Duke University
David M. Blei
David M. Blei Columbia University
Xueyang Fu
Xueyang Fu University of Science and Technology of China
Michael I. Jordan
Michael I. Jordan University of California, Berkeley
David B. Dunson
David B. Dunson Duke University
Mingyuan Zhou
Mingyuan Zhou The University of Texas at Austin
Felix Waldhauser
Felix Waldhauser Lamont-Doherty Earth Observatory
Dustin Tran
Dustin Tran Google (United States)

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