An Empirical Study of Pre-trained Model Selection for Out-of-Distribution Generalization and Calibration

An Empirical Study of Pre-trained Model Selection for Out-of-Distribution Generalization and Calibration

17 July 2023

Hiroki Naganuma

Ryuichiro Hataya

Ioannis Mitliagkas

Papers citing "An Empirical Study of Pre-trained Model Selection for Out-of-Distribution Generalization and Calibration"

9 / 9 papers shown

Title
Towards Understanding Variants of Invariant Risk Minimization through the Lens of Calibration Kotaro Yoshida Hiroki Naganuma 44 1 0 31 Jan 2024
Battle of the Backbones: A Large-Scale Comparison of Pretrained Models across Computer Vision Tasks Micah Goldblum Hossein Souri Renkun Ni Manli Shu Viraj Prabhu ... Adrien Bardes Judy Hoffman Ramalingam Chellappa Andrew Gordon Wilson Tom Goldstein VLM 50 30 0 30 Oct 2023
Masked Autoencoders Are Scalable Vision Learners Kaiming He Xinlei Chen Saining Xie Yanghao Li Piotr Dollár Ross B. Girshick ViT TPM 243 5,353 0 11 Nov 2021
ResNet strikes back: An improved training procedure in timm Ross Wightman Hugo Touvron Hervé Jégou AI4TS 189 403 0 01 Oct 2021
MLP-Mixer: An all-MLP Architecture for Vision Ilya O. Tolstikhin N. Houlsby Alexander Kolesnikov Lucas Beyer Xiaohua Zhai ... Andreas Steiner Daniel Keysers Jakob Uszkoreit Mario Lucic Alexey Dosovitskiy 222 2,132 0 04 May 2021
Emerging Properties in Self-Supervised Vision Transformers Mathilde Caron Hugo Touvron Ishan Misra Hervé Jégou Julien Mairal Piotr Bojanowski Armand Joulin 265 4,299 0 29 Apr 2021
Improving model calibration with accuracy versus uncertainty optimization R. Krishnan Omesh Tickoo UQCV 166 140 0 14 Dec 2020
Out-of-Distribution Generalization via Risk Extrapolation (REx) David M. Krueger Ethan Caballero J. Jacobsen Amy Zhang Jonathan Binas Dinghuai Zhang Rémi Le Priol Aaron Courville OOD 194 759 0 02 Mar 2020
Scaling Laws for Neural Language Models Jared Kaplan Sam McCandlish T. Henighan Tom B. Brown B. Chess R. Child Scott Gray Alec Radford Jeff Wu Dario Amodei 215 3,054 0 23 Jan 2020