John Paisley

16

Papers

11

Total Citations

Papers (16)

Gaussian Process Neural Additive Models

Sparse Inducing Points in Deep Gaussian Processes: Enhancing Modeling with Denoising Diffusion Variational Inference

Removing Rain From Single Images via a Deep Detail Network

Pan-Sharpening With a Hyper-Laplacian Penalty

PanNet: A Deep Network Architecture for Pan-Sharpening

JPEG Artifacts Reduction via Deep Convolutional Sparse Coding

Deep Blind Hyperspectral Image Fusion

Variational Inference via $\chi$ Upper Bound Minimization

Accurate Uncertainty Estimation and Decomposition in Ensemble Learning

A state-space model for inferring effective connectivity of latent neural dynamics from simultaneous EEG/fMRI

Landmarking Manifolds with Gaussian Processes

Markov Mixed Membership Models

Markov Latent Feature Models

CRVI: Convex Relaxation for Variational Inference

Deep Bayesian Nonparametric Tracking

Random Function Priors for Correlation Modeling