
MaxAffine Spline Insights Into Deep Network Pruning
In this paper, we study the importance of pruning in Deep Networks (DNs)...
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SASSI – SuperPixelated Adaptive SpatioSpectral Imaging
We introduce a novel videorate hyperspectral imager with high spatial, ...
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Interpretable Image Clustering via DiffeomorphismAware KMeans
We design an interpretable clustering algorithm aware of the nonlinear s...
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Scalable Neural Tangent Kernel of Recurrent Architectures
Kernels derived from deep neural networks (DNNs) in the infinitewidth p...
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Provable Finite Data Generalization with Group Autoencoder
Deep Autoencoders (AEs) provide a versatile framework to learn a compres...
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ComputerAided Personalized Education
The shortage of people trained in STEM fields is becoming acute, and uni...
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The Recurrent Neural Tangent Kernel
The study of deep networks (DNs) in the infinitewidth limit, via the so...
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VarFA: A Variational Factor Analysis Framework For Efficient Bayesian Learning Analytics
We propose VarFA, a variational inference factor analysis framework that...
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MaxAffine Spline Insights into Deep Generative Networks
We connect a large class of Generative Deep Networks (GDNs) with spline ...
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Dual Dynamic Inference: Enabling More Efficient, Adaptive and Controllable Deep Inference
Stateoftheart convolutional neural networks (CNNs) yield recordbreak...
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A Hessian Based Complexity Measure for Deep Networks
Deep (neural) networks have been applied productively in a wide range of...
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The Geometry of Deep Networks: Power Diagram Subdivision
We study the geometry of deep (neural) networks (DNs) with piecewise aff...
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A Spline Theory of Deep Networks (Extended Version)
We build a rigorous bridge between deep networks (DNs) and approximation...
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SemiSupervised Learning Enabled by Multiscale Deep Neural Network Inversion
Deep Neural Networks (DNNs) provide stateoftheart solutions in severa...
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Overcomplete Frame Thresholding for Acoustic Scene Analysis
In this work, we derive a generic overcomplete frame thresholding scheme...
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Deep Neural Networks
Deep Neural Networks (DNNs) are universal function approximators providi...
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FlatCam: Thin, BareSensor Cameras using Coded Aperture and Computation
FlatCam is a thin formfactor lensless camera that consists of a coded m...
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Fast Sublinear Sparse Representation using Shallow Tree Matching Pursuit
Sparse approximations using highly overcomplete dictionaries is a state...
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The STONE Transform: MultiResolution Image Enhancement and RealTime Compressive Video
Compressed sensing enables the reconstruction of highresolution signals...
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Richard Baraniuk
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