John Paisley

29 papers · 2011–2025 · 10 conferences · across top CS/AI conferences

Achievements

+13 more ↓

🌍 Conference Polyglot (10) 🐣 Hot Topic Early Bird 🌉 Interdisciplinary Bridge 🧭 Keyword Pioneer 🏃 Academic Marathon (14)

🐣 Hot Topic Early Bird 🗺️ Taxonomy Completionist (40) 🌉 Interdisciplinary Bridge 🔬 Deep Specialist (10) 🤝 Dynamic Duo (10) 🌱 Topic Pioneer 🏆 Keyword Champion (2) 🗃️ Keyword Collector (102) ⚡ Prolific Year (5) 🚀 Conference Pioneer 💎 Century Club (29) 🔥 Unstoppable (10) 📈 Trend Setter

Conferences

ICML (8) AISTATS (6) ICCV (4) NIPS (3) AAAI (2) UAI (2) CVPR (1) ECCV (1) IJCAI (1) JMLR (1)

Top co-authors

Xinghao Ding (10) Delu Zeng (8) Yue Huang (7) Aonan Zhang (5) Jian Xu (3) Junmei Yang (3) Chong Wang (3) Xueyang Fu (3) David Blei (3) Shian Du (2)

Research topics

Bayesian & Probabilistic (1)

Keywords

variational inference (8) bayesian nonparametrics (7) hierarchical dirichlet process (3) convolutional neural network (3) image restoration (3) topic model (2) latent variable model (2) deep neural network (2) posterior distribution (2) markov chain monte carlo (2) markov chain (2) stochastic variational inference (2) gaussian process (2) image fusion (2) stochastic optimization (2) sparse representation (2) topic modeling (2) sparse coding (2) image denoising (2) mixed membership model (2)

Papers

Variational Learning of Gaussian Process Latent Variable Models through Stochastic Gradient Annealed Importance Sampling UAI 2025 Bayesian Gaussian Process ODEs via Double Normalizing Flows AISTATS 2025 Dequantified Diffusion-Schrödinger Bridge for Density Ratio Estimation ICML 2025 Sparse Inducing Points in Deep Gaussian Processes: Enhancing Modeling with Denoising Diffusion Variational Inference ICML 2024 Gaussian Process Neural Additive Models AAAI 2024 Self-Supervised Image Denoising Using Implicit Deep Denoiser Prior AAAI 2023 Risk Bounds for Low Cost Bipartite Ranking UAI 2020 JPEG Artifacts Reduction via Deep Convolutional Sparse Coding ICCV 2019 Accurate Uncertainty Estimation and Decomposition in Ensemble Learning NIPS 2019 Random Function Priors for Correlation Modeling ICML 2019 A state-space model for inferring effective connectivity of latent neural dynamics from simultaneous EEG/fMRI NIPS 2019 Deep Blind Hyperspectral Image Fusion ICCV 2019 MEnet: A Metric Expression Network for Salient Object Segmentation IJCAI 2018 CRVI: Convex Relaxation for Variational Inference ICML 2018 Deep Bayesian Nonparametric Tracking ICML 2018 A Segmentation-aware Deep Fusion Network for Compressed Sensing MRI ECCV 2018 PanNet: A Deep Network Architecture for Pan-Sharpening ICCV 2017 Removing Rain From Single Images via a Deep Detail Network CVPR 2017 Variational Inference via $\chi$ Upper Bound Minimization NIPS 2017 Markov Latent Feature Models ICML 2016 Stochastic Variational Inference for the HDP-HMM AISTATS 2016 Markov Mixed Membership Models ICML 2015 Landmarking Manifolds with Gaussian Processes ICML 2015 Pan-Sharpening With a Hyper-Laplacian Penalty ICCV 2015 Pan-sharpening with a Bayesian nonparametric dictionary learning model AISTATS 2014 Stochastic Variational Inference JMLR 2013 Stick-Breaking Beta Processes and the Poisson Process AISTATS 2012 Online Variational Inference for the Hierarchical Dirichlet Process AISTATS 2011 The Discrete Infinite Logistic Normal Distribution for Mixed-Membership Modeling AISTATS 2011