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An Impartial Take to the CNN vs Transformer Robustness Contest


Jul 22, 2022
Francesco Pinto, Philip H. S. Torr, Puneet K. Dokania

* ECCV 2022 

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Sample-dependent Adaptive Temperature Scaling for Improved Calibration


Jul 22, 2022
Tom Joy, Francesco Pinto, Ser-Nam Lim, Philip H. S. Torr, Puneet K. Dokania


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RegMixup: Mixup as a Regularizer Can Surprisingly Improve Accuracy and Out Distribution Robustness


Jun 29, 2022
Francesco Pinto, Harry Yang, Ser-Nam Lim, Philip H. S. Torr, Puneet K. Dokania

* 22 pages, 18 figures 

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Catastrophic overfitting is a bug but also a feature


Jun 16, 2022
Guillermo Ortiz-Jiménez, Pau de Jorge, Amartya Sanyal, Adel Bibi, Puneet K. Dokania, Pascal Frossard, Gregory Rogéz, Philip H. S. Torr

* 24 pages, 19 figures, 1 table. Work partially presented at Adversarial Machine Learning Workshop at ICML 2022 

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Make Some Noise: Reliable and Efficient Single-Step Adversarial Training


Feb 02, 2022
Pau de Jorge, Adel Bibi, Riccardo Volpi, Amartya Sanyal, Philip H. S. Torr, Grégory Rogez, Puneet K. Dokania


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ANCER: Anisotropic Certification via Sample-wise Volume Maximization


Jul 20, 2021
Francisco Eiras, Motasem Alfarra, M. Pawan Kumar, Philip H. S. Torr, Puneet K. Dokania, Bernard Ghanem, Adel Bibi

* First two authors and the last one contributed equally to this work 

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No Cost Likelihood Manipulation at Test Time for Making Better Mistakes in Deep Networks


Apr 01, 2021
Shyamgopal Karthik, Ameya Prabhu, Puneet K. Dokania, Vineet Gandhi


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On Batch Normalisation for Approximate Bayesian Inference


Dec 24, 2020
Jishnu Mukhoti, Puneet K. Dokania, Philip H. S. Torr, Yarin Gal


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