Papers
Communities
Events
Blog
Pricing
Search
Open menu
Home
Papers
2210.12760
Cited By
On double-descent in uncertainty quantification in overparametrized models
23 October 2022
Lucas Clarté
Bruno Loureiro
Florent Krzakala
Lenka Zdeborová
UQCV
Re-assign community
ArXiv
PDF
HTML
Papers citing
"On double-descent in uncertainty quantification in overparametrized models"
50 / 61 papers shown
Title
A Theory of Non-Linear Feature Learning with One Gradient Step in Two-Layer Neural Networks
Behrad Moniri
Donghwan Lee
Hamed Hassani
Yan Sun
MLT
84
22
0
11 Oct 2023
Universality laws for Gaussian mixtures in generalized linear models
Yatin Dandi
Ludovic Stephan
Florent Krzakala
Bruno Loureiro
Lenka Zdeborová
FedML
72
21
0
17 Feb 2023
Deterministic equivalent and error universality of deep random features learning
Dominik Schröder
Hugo Cui
Daniil Dmitriev
Bruno Loureiro
MLT
71
28
0
01 Feb 2023
Quantitative deterministic equivalent of sample covariance matrices with a general dependence structure
Clément Chouard
49
6
0
23 Nov 2022
Learning curves for the multi-class teacher-student perceptron
Elisabetta Cornacchia
Francesca Mignacco
R. Veiga
Cédric Gerbelot
Bruno Loureiro
Lenka Zdeborová
79
21
0
22 Mar 2022
Universality of empirical risk minimization
Andrea Montanari
Basil Saeed
OOD
63
75
0
17 Feb 2022
Theoretical characterization of uncertainty in high-dimensional linear classification
Lucas Clarté
Bruno Loureiro
Florent Krzakala
Lenka Zdeborová
65
20
0
07 Feb 2022
Fluctuations, Bias, Variance & Ensemble of Learners: Exact Asymptotics for Convex Losses in High-Dimension
Bruno Loureiro
Cédric Gerbelot
Maria Refinetti
G. Sicuro
Florent Krzakala
72
27
0
31 Jan 2022
Graph-based Approximate Message Passing Iterations
Cédric Gerbelot
Raphael Berthier
80
47
0
24 Sep 2021
Structured Stochastic Gradient MCMC
Antonios Alexos
Alex Boyd
Stephan Mandt
BDL
40
13
0
19 Jul 2021
Performance of Bayesian linear regression in a model with mismatch
Jean Barbier
Wei-Kuo Chen
D. Panchenko
Manuel Sáenz
71
22
0
14 Jul 2021
A Survey of Uncertainty in Deep Neural Networks
J. Gawlikowski
Cedrique Rovile Njieutcheu Tassi
Mohsin Ali
Jongseo Lee
Matthias Humt
...
R. Roscher
Muhammad Shahzad
Wen Yang
R. Bamler
Xiaoxiang Zhu
BDL
UQCV
OOD
229
1,150
0
07 Jul 2021
Laplace Redux -- Effortless Bayesian Deep Learning
Erik A. Daxberger
Agustinus Kristiadi
Alexander Immer
Runa Eschenhagen
Matthias Bauer
Philipp Hennig
BDL
UQCV
218
313
0
28 Jun 2021
Hessian Eigenspectra of More Realistic Nonlinear Models
Zhenyu Liao
Michael W. Mahoney
62
31
0
02 Mar 2021
Learning curves of generic features maps for realistic datasets with a teacher-student model
Bruno Loureiro
Cédric Gerbelot
Hugo Cui
Sebastian Goldt
Florent Krzakala
M. Mézard
Lenka Zdeborová
99
138
0
16 Feb 2021
Don't Just Blame Over-parametrization for Over-confidence: Theoretical Analysis of Calibration in Binary Classification
Yu Bai
Song Mei
Haiquan Wang
Caiming Xiong
51
42
0
15 Feb 2021
A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges
Moloud Abdar
Farhad Pourpanah
Sadiq Hussain
Dana Rezazadegan
Li Liu
...
Xiaochun Cao
Abbas Khosravi
U. Acharya
V. Makarenkov
S. Nahavandi
BDL
UQCV
341
1,922
0
12 Nov 2020
Strong replica symmetry for high-dimensional disordered log-concave Gibbs measures
Jean Barbier
D. Panchenko
Manuel Sáenz
60
10
0
27 Sep 2020
Hands-on Bayesian Neural Networks -- a Tutorial for Deep Learning Users
Laurent Valentin Jospin
Wray Buntine
F. Boussaïd
Hamid Laga
Bennamoun
OOD
BDL
UQCV
84
628
0
14 Jul 2020
The Gaussian equivalence of generative models for learning with shallow neural networks
Sebastian Goldt
Bruno Loureiro
Galen Reeves
Florent Krzakala
M. Mézard
Lenka Zdeborová
BDL
83
103
0
25 Jun 2020
Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness
Jeremiah Zhe Liu
Zi Lin
Shreyas Padhy
Dustin Tran
Tania Bedrax-Weiss
Balaji Lakshminarayanan
UQCV
BDL
171
451
0
17 Jun 2020
Generalization error in high-dimensional perceptrons: Approaching Bayes error with convex optimization
Benjamin Aubin
Florent Krzakala
Yue M. Lu
Lenka Zdeborová
61
54
0
11 Jun 2020
Optimal Regularization Can Mitigate Double Descent
Preetum Nakkiran
Prayaag Venkat
Sham Kakade
Tengyu Ma
81
133
0
04 Mar 2020
Double Trouble in Double Descent : Bias and Variance(s) in the Lazy Regime
Stéphane dÁscoli
Maria Refinetti
Giulio Biroli
Florent Krzakala
154
152
0
02 Mar 2020
The estimation error of general first order methods
Michael Celentano
Andrea Montanari
Yuchen Wu
48
45
0
28 Feb 2020
Being Bayesian, Even Just a Bit, Fixes Overconfidence in ReLU Networks
Agustinus Kristiadi
Matthias Hein
Philipp Hennig
BDL
UQCV
86
287
0
24 Feb 2020
Calibrating Deep Neural Networks using Focal Loss
Jishnu Mukhoti
Viveka Kulharia
Amartya Sanyal
Stuart Golodetz
Philip Torr
P. Dokania
UQCV
81
463
0
21 Feb 2020
Generalisation error in learning with random features and the hidden manifold model
Federica Gerace
Bruno Loureiro
Florent Krzakala
M. Mézard
Lenka Zdeborová
67
169
0
21 Feb 2020
On Last-Layer Algorithms for Classification: Decoupling Representation from Uncertainty Estimation
N. Brosse
C. Riquelme
Alice Martin
Sylvain Gelly
Eric Moulines
BDL
OOD
UQCV
92
33
0
22 Jan 2020
Deep Double Descent: Where Bigger Models and More Data Hurt
Preetum Nakkiran
Gal Kaplun
Yamini Bansal
Tristan Yang
Boaz Barak
Ilya Sutskever
121
942
0
04 Dec 2019
A Model of Double Descent for High-dimensional Binary Linear Classification
Zeyu Deng
A. Kammoun
Christos Thrampoulidis
85
146
0
13 Nov 2019
The generalization error of random features regression: Precise asymptotics and double descent curve
Song Mei
Andrea Montanari
83
635
0
14 Aug 2019
Benign Overfitting in Linear Regression
Peter L. Bartlett
Philip M. Long
Gábor Lugosi
Alexander Tsigler
MLT
86
776
0
26 Jun 2019
Universality in Learning from Linear Measurements
Ehsan Abbasi
Fariborz Salehi
B. Hassibi
124
22
0
20 Jun 2019
The spiked matrix model with generative priors
Benjamin Aubin
Bruno Loureiro
Antoine Maillard
Florent Krzakala
Lenka Zdeborová
57
53
0
29 May 2019
Eigenvalue distribution of nonlinear models of random matrices
L. Benigni
Sandrine Péché
60
27
0
05 Apr 2019
Surprises in High-Dimensional Ridgeless Least Squares Interpolation
Trevor Hastie
Andrea Montanari
Saharon Rosset
Robert Tibshirani
188
743
0
19 Mar 2019
A Simple Baseline for Bayesian Uncertainty in Deep Learning
Wesley J. Maddox
T. Garipov
Pavel Izmailov
Dmitry Vetrov
A. Wilson
BDL
UQCV
84
808
0
07 Feb 2019
Reconciling modern machine learning practice and the bias-variance trade-off
M. Belkin
Daniel J. Hsu
Siyuan Ma
Soumik Mandal
232
1,650
0
28 Dec 2018
Why ReLU networks yield high-confidence predictions far away from the training data and how to mitigate the problem
Matthias Hein
Maksym Andriushchenko
Julian Bitterwolf
OODD
167
558
0
13 Dec 2018
A jamming transition from under- to over-parametrization affects loss landscape and generalization
S. Spigler
Mario Geiger
Stéphane dÁscoli
Levent Sagun
Giulio Biroli
Matthieu Wyart
61
150
0
22 Oct 2018
The jamming transition as a paradigm to understand the loss landscape of deep neural networks
Mario Geiger
S. Spigler
Stéphane dÁscoli
Levent Sagun
Marco Baity-Jesi
Giulio Biroli
Matthieu Wyart
51
143
0
25 Sep 2018
The committee machine: Computational to statistical gaps in learning a two-layers neural network
Benjamin Aubin
Antoine Maillard
Jean Barbier
Florent Krzakala
N. Macris
Lenka Zdeborová
77
106
0
14 Jun 2018
On the Spectrum of Random Features Maps of High Dimensional Data
Zhenyu Liao
Romain Couillet
57
51
0
30 May 2018
Entropy and mutual information in models of deep neural networks
Marylou Gabrié
Andre Manoel
Clément Luneau
Jean Barbier
N. Macris
Florent Krzakala
Lenka Zdeborová
71
180
0
24 May 2018
The phase transition for the existence of the maximum likelihood estimate in high-dimensional logistic regression
Emmanuel J. Candes
Pragya Sur
61
140
0
25 Apr 2018
A modern maximum-likelihood theory for high-dimensional logistic regression
Pragya Sur
Emmanuel J. Candes
55
288
0
19 Mar 2018
Optimal Errors and Phase Transitions in High-Dimensional Generalized Linear Models
Jean Barbier
Florent Krzakala
N. Macris
Léo Miolane
Lenka Zdeborová
82
265
0
10 Aug 2017
On Calibration of Modern Neural Networks
Chuan Guo
Geoff Pleiss
Yu Sun
Kilian Q. Weinberger
UQCV
299
5,833
0
14 Jun 2017
A Random Matrix Approach to Neural Networks
Cosme Louart
Zhenyu Liao
Romain Couillet
65
161
0
17 Feb 2017
1
2
Next