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MaGNET: Uniform Sampling from Deep Generative Network Manifolds Without Retraining


Oct 18, 2021
Ahmed Imtiaz Humayun, Randall Balestriero, Richard Baraniuk

* 13 pages, 14 pages Appendix, 23 figures 

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Thermal Image Processing via Physics-Inspired Deep Networks


Aug 25, 2021
Vishwanath Saragadam, Akshat Dave, Ashok Veeraraghavan, Richard Baraniuk

* Accepted to 2nd ICCV workshop on Learning for Computational Imaging (LCI) 

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Double Descent and Other Interpolation Phenomena in GANs


Jun 07, 2021
Lorenzo Luzi, Yehuda Dar, Richard Baraniuk


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Math Operation Embeddings for Open-ended Solution Analysis and Feedback


Apr 25, 2021
Mengxue Zhang, Zichao Wang, Richard Baraniuk, Andrew Lan


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Fast Jacobian-Vector Product for Deep Networks


Apr 01, 2021
Randall Balestriero, Richard Baraniuk


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Max-Affine Spline Insights Into Deep Network Pruning


Jan 07, 2021
Randall Balestriero, Haoran You, Zhihan Lu, Yutong Kou, Yingyan Lin, Richard Baraniuk


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SASSI -- Super-Pixelated Adaptive Spatio-Spectral Imaging


Dec 28, 2020
Vishwanath Saragadam, Michael DeZeeuw, Richard Baraniuk, Ashok Veeraraghavan, Aswin Sankaranarayanan


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Interpretable Image Clustering via Diffeomorphism-Aware K-Means


Dec 16, 2020
Romain Cosentino, Randall Balestriero, Yanis Bahroun, Anirvan Sengupta, Richard Baraniuk, Behnaam Aazhang


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Scalable Neural Tangent Kernel of Recurrent Architectures


Dec 09, 2020
Sina Alemohammad, Randall Balestriero, Zichao Wang, Richard Baraniuk


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Provable Finite Data Generalization with Group Autoencoder


Sep 20, 2020
Romain Cosentino, Randall Balestriero, Richard Baraniuk, Behnaam Aazhang


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The Recurrent Neural Tangent Kernel


Jun 18, 2020
Sina Alemohammad, Zichao Wang, Randall Balestriero, Richard Baraniuk


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VarFA: A Variational Factor Analysis Framework For Efficient Bayesian Learning Analytics


May 27, 2020
Zichao Wang, Yi Gu, Andrew Lan, Richard Baraniuk


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Max-Affine Spline Insights into Deep Generative Networks


Feb 26, 2020
Randall Balestriero, Sebastien Paris, Richard Baraniuk


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Dual Dynamic Inference: Enabling More Efficient, Adaptive and Controllable Deep Inference


Jul 17, 2019
Yue Wang, Jianghao Shen, Ting-Kuei Hu, Pengfei Xu, Tan Nguyen, Richard Baraniuk, Zhangyang Wang, Yingyan Lin


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A Hessian Based Complexity Measure for Deep Networks


May 30, 2019
Hamid Javadi, Randall Balestriero, Richard Baraniuk

* 13 pages, 8 figures 

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The Geometry of Deep Networks: Power Diagram Subdivision


May 21, 2019
Randall Balestriero, Romain Cosentino, Behnaam Aazhang, Richard Baraniuk


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Mad Max: Affine Spline Insights into Deep Learning


Jul 25, 2018
Randall Balestriero, Richard Baraniuk


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Semi-Supervised Learning Enabled by Multiscale Deep Neural Network Inversion


Feb 27, 2018
Randall Balestriero, Herve Glotin, Richard Baraniuk


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Overcomplete Frame Thresholding for Acoustic Scene Analysis


Dec 25, 2017
Romain Cosentino, Randall Balestriero, Richard Baraniuk, Ankit Patel


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Deep Neural Networks


Nov 06, 2017
Randall Balestriero, Richard Baraniuk

* Technical Report 

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FlatCam: Thin, Bare-Sensor Cameras using Coded Aperture and Computation


Jan 27, 2016
M. Salman Asif, Ali Ayremlou, Aswin Sankaranarayanan, Ashok Veeraraghavan, Richard Baraniuk

* 12 pages, 10 figures 

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Fast Sublinear Sparse Representation using Shallow Tree Matching Pursuit


Dec 01, 2014
Ali Ayremlou, Thomas Goldstein, Ashok Veeraraghavan, Richard Baraniuk


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The STONE Transform: Multi-Resolution Image Enhancement and Real-Time Compressive Video


Nov 15, 2013
Tom Goldstein, Lina Xu, Kevin F. Kelly, Richard Baraniuk


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