
Further Analysis of Outlier Detection with Deep Generative Models
The recent, counterintuitive discovery that deep generative models (DGM...
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CycleGT: Unsupervised GraphtoText and TexttoGraph Generation via Cycle Training
Two important tasks at the intersection of knowledge graphs and natural ...
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The Usual Suspects? Reassessing Blame for VAE Posterior Collapse
In narrow asymptotic settings Gaussian VAE models of continuous data hav...
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Single Image Reflection Removal Exploiting Misaligned Training Data and Network Enhancements
Removing undesirable reflections from a single image captured through a ...
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Diagnosing and Enhancing VAE Models
Although variational autoencoders (VAEs) represent a widely influential ...
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Image Smoothing via Unsupervised Learning
Image smoothing represents a fundamental component of many disparate com...
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Compressing Neural Networks using the Variational Information Bottleneck
Neural networks can be compressed to reduce memory and computational req...
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A Generic Deep Architecture for Single Image Reflection Removal and Image Smoothing
This paper proposes a deep neural network structure that exploits edge i...
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Revisiting Deep Intrinsic Image Decompositions
While invaluable for many computer vision applications, decomposing a na...
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PseudoBayesian Robust PCA: Algorithms and Analyses
Commonly used in computer vision and other applications, robust PCA repr...
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Unsupervised Extraction of Video Highlights Via Robust Recurrent Autoencoders
With the growing popularity of shortform video sharing platforms such a...
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NonConvex Rank Minimization via an Empirical Bayesian Approach
In many applications that require matrix solutions of minimal rank, the ...
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NonUniform Blind Deblurring with a SpatiallyAdaptive Sparse Prior
Typical blur from camera shake often deviates from the standard uniform ...
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Revisiting Bayesian Blind Deconvolution
Blind deconvolution involves the estimation of a sharp signal or image g...
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Image SuperResolution via Sparse Bayesian Modeling of Natural Images
Image superresolution (SR) is one of the longstanding and active topic...
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DualSpace Analysis of the Sparse Linear Model
Sparse linear (or generalized linear) models combine a standard likeliho...
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David Wipf
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