On double-descent in uncertainty quantification in overparametrized
models

On double-descent in uncertainty quantification in overparametrized models

23 October 2022

Florent Krzakala

Lenka Zdeborová

Papers citing "On double-descent in uncertainty quantification in overparametrized models"

11 / 61 papers shown

Title
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 840 5,821 0 05 Dec 2016
Precise Error Analysis of Regularized M-estimators in High-dimensions Christos Thrampoulidis Ehsan Abbasi B. Hassibi 189 220 0 23 Jan 2016
Statistical physics of inference: Thresholds and algorithms Lenka Zdeborová Florent Krzakala AI4CE 81 426 0 08 Nov 2015
High-Dimensional Asymptotics of Prediction: Ridge Regression and Classification Yan Sun Stefan Wager 108 287 0 10 Jul 2015
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 821 9,318 0 06 Jun 2015
Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images Anh Totti Nguyen J. Yosinski Jeff Clune AAML 169 3,271 0 05 Dec 2014
High Dimensional Robust M-Estimation: Asymptotic Variance via Approximate Message Passing D. Donoho Andrea Montanari 218 221 0 28 Oct 2013
A framework to characterize performance of LASSO algorithms M. Stojnic 267 128 0 29 Mar 2013
The LASSO risk for gaussian matrices Mohsen Bayati Andrea Montanari 186 318 0 16 Aug 2010
The spectrum of kernel random matrices N. Karoui 160 224 0 04 Jan 2010
Observed Universality of Phase Transitions in High-Dimensional Geometry, with Implications for Modern Data Analysis and Signal Processing D. Donoho Jared Tanner 90 464 0 14 Jun 2009