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Guha Balakrishnan
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SplineCam: Exact Visualization and Characterization of Deep Network Geometry and Decision Boundaries


Feb 24, 2023
Ahmed Imtiaz Humayun, Randall Balestriero, Guha Balakrishnan, Richard Baraniuk

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* 11 pages, 20 figures 
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Towards causally linking architectural parametrizations to algorithmic bias in neural networks


Feb 07, 2023
Hao Liang, Josue Ortega Caro, Vikram Maheshri, Ankit B. Patel, Guha Balakrishnan

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* 23 pages, 15 figures, 2 tables 
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WIRE: Wavelet Implicit Neural Representations


Jan 05, 2023
Vishwanath Saragadam, Daniel LeJeune, Jasper Tan, Guha Balakrishnan, Ashok Veeraraghavan, Richard G. Baraniuk

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Leveling Down in Computer Vision: Pareto Inefficiencies in Fair Deep Classifiers


Mar 31, 2022
Dominik Zietlow, Michael Lohaus, Guha Balakrishnan, Matthäus Kleindessner, Francesco Locatello, Bernhard Schölkopf, Chris Russell

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MINER: Multiscale Implicit Neural Representations


Feb 07, 2022
Vishwanath Saragadam, Jasper Tan, Guha Balakrishnan, Richard G. Baraniuk, Ashok Veeraraghavan

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Rayleigh EigenDirections (REDs): GAN latent space traversals for multidimensional features


Jan 25, 2022
Guha Balakrishnan, Raghudeep Gadde, Aleix Martinez, Pietro Perona

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Matched sample selection with GANs for mitigating attribute confounding


Mar 24, 2021
Chandan Singh, Guha Balakrishnan, Pietro Perona

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When and Why Test-Time Augmentation Works


Nov 23, 2020
Divya Shanmugam, Davis Blalock, Guha Balakrishnan, John Guttag

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Towards causal benchmarking of bias in face analysis algorithms


Jul 13, 2020
Guha Balakrishnan, Yuanjun Xiong, Wei Xia, Pietro Perona

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* Long-form version of ECCV 2020 paper 
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