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An Underexplored Dilemma between Confidence and Calibration in Quantized Neural Networks


Dec 02, 2021
Guoxuan Xia, Sangwon Ha, Tiago Azevedo, Partha Maji

* Accepted at I (Still) Can't Believe It's Not Better Workshop at NeurIPS 2021 

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On Efficient Uncertainty Estimation for Resource-Constrained Mobile Applications


Dec 01, 2021
Johanna Rock, Tiago Azevedo, René de Jong, Daniel Ruiz-Muñoz, Partha Maji

* 7 pages; Accepted at the Bayesian Deep Learning Workshop, NeurIPS 2021 

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Towards Efficient Point Cloud Graph Neural Networks Through Architectural Simplification


Aug 13, 2021
Shyam A. Tailor, René de Jong, Tiago Azevedo, Matthew Mattina, Partha Maji

* 8 pages. Accepted to the Deep Learning for Geometric Computing Workshop at ICCV 2021 

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Stochastic-Shield: A Probabilistic Approach Towards Training-Free Adversarial Defense in Quantized CNNs


May 13, 2021
Lorena Qendro, Sangwon Ha, René de Jong, Partha Maji


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On the Effects of Quantisation on Model Uncertainty in Bayesian Neural Networks


Feb 22, 2021
Martin Ferianc, Partha Maji, Matthew Mattina, Miguel Rodrigues

* Code at: https://github.com/martinferianc/quantised-bayesian-nets 

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Stochastic-YOLO: Efficient Probabilistic Object Detection under Dataset Shifts


Sep 07, 2020
Tiago Azevedo, René de Jong, Partha Maji

* 9 pages, 7 figures 

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Efficient Winograd or Cook-Toom Convolution Kernel Implementation on Widely Used Mobile CPUs


Mar 04, 2019
Partha Maji, Andrew Mundy, Ganesh Dasika, Jesse Beu, Matthew Mattina, Robert Mullins

* HPCA.EMC2 Feb 17, 2019 

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