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2010.16402
Cited By
Why Do Better Loss Functions Lead to Less Transferable Features?
30 October 2020
Simon Kornblith
Ting-Li Chen
Honglak Lee
Mohammad Norouzi
FaML
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Papers citing
"Why Do Better Loss Functions Lead to Less Transferable Features?"
23 / 23 papers shown
Title
A Reality Check of Vision-Language Pre-training in Radiology: Have We Progressed Using Text?
Julio Silva-Rodríguez
Jose Dolz
Ismail ben Ayed
VLM
MedIm
38
0
0
07 Apr 2025
CLOSER: Towards Better Representation Learning for Few-Shot Class-Incremental Learning
Junghun Oh
Sungyong Baik
Kyoung Mu Lee
CLL
34
3
0
08 Oct 2024
DualFed: Enjoying both Generalization and Personalization in Federated Learning via Hierachical Representations
Guogang Zhu
Xuefeng Liu
Jianwei Niu
Shaojie Tang
Xinghao Wu
Jiayuan Zhang
AI4CE
47
1
0
25 Jul 2024
KITE: A Kernel-based Improved Transferability Estimation Method
Yunhui Guo
45
0
0
01 May 2024
Get the Best of Both Worlds: Improving Accuracy and Transferability by Grassmann Class Representation
Haoqi Wang
Zhizhong Li
Wayne Zhang
15
2
0
03 Aug 2023
Improving neural network representations using human similarity judgments
Lukas Muttenthaler
Lorenz Linhardt
Jonas Dippel
Robert A. Vandermeulen
Katherine L. Hermann
Andrew Kyle Lampinen
Simon Kornblith
40
29
0
07 Jun 2023
Quantifying the Variability Collapse of Neural Networks
Jing-Xue Xu
Haoxiong Liu
36
4
0
06 Jun 2023
Joint Adaptive Representations for Image-Language Learning
A. Piergiovanni
A. Angelova
VLM
26
0
0
31 May 2023
Similarity of Neural Network Models: A Survey of Functional and Representational Measures
Max Klabunde
Tobias Schumacher
M. Strohmaier
Florian Lemmerich
52
64
0
10 May 2023
Preemptively Pruning Clever-Hans Strategies in Deep Neural Networks
Lorenz Linhardt
Klaus-Robert Muller
G. Montavon
AAML
23
7
0
12 Apr 2023
Principled and Efficient Transfer Learning of Deep Models via Neural Collapse
Xiao Li
Sheng Liu
Jin-li Zhou
Xin Lu
C. Fernandez‐Granda
Zhihui Zhu
Q. Qu
AAML
28
18
0
23 Dec 2022
Hidden State Variability of Pretrained Language Models Can Guide Computation Reduction for Transfer Learning
Shuo Xie
Jiahao Qiu
Ankita Pasad
Li Du
Qing Qu
Hongyuan Mei
35
16
0
18 Oct 2022
Are All Losses Created Equal: A Neural Collapse Perspective
Jinxin Zhou
Chong You
Xiao Li
Kangning Liu
Sheng Liu
Qing Qu
Zhihui Zhu
36
58
0
04 Oct 2022
Neural Collapse with Normalized Features: A Geometric Analysis over the Riemannian Manifold
Can Yaras
Peng Wang
Zhihui Zhu
Laura Balzano
Qing Qu
25
41
0
19 Sep 2022
Neural Collapse: A Review on Modelling Principles and Generalization
Vignesh Kothapalli
21
71
0
08 Jun 2022
Discriminability-Transferability Trade-Off: An Information-Theoretic Perspective
Quan Cui
Bingchen Zhao
Zhao-Min Chen
Borui Zhao
Renjie Song
Jiajun Liang
Boyan Zhou
Osamu Yoshie
24
18
0
08 Mar 2022
On the Optimization Landscape of Neural Collapse under MSE Loss: Global Optimality with Unconstrained Features
Jinxin Zhou
Xiao Li
Tian Ding
Chong You
Qing Qu
Zhihui Zhu
24
97
0
02 Mar 2022
Deconfounded Representation Similarity for Comparison of Neural Networks
Tianyu Cui
Yogesh Kumar
Pekka Marttinen
Samuel Kaski
CML
27
13
0
31 Jan 2022
Contrastive Object Detection Using Knowledge Graph Embeddings
Christopher Lang
Alexander Braun
Abhinav Valada
18
8
0
21 Dec 2021
Contrastive Attraction and Contrastive Repulsion for Representation Learning
Huangjie Zheng
Xu Chen
Jiangchao Yao
Hongxia Yang
Chunyuan Li
Ya-Qin Zhang
Hao Zhang
Ivor Tsang
Jingren Zhou
Mingyuan Zhou
SSL
42
12
0
08 May 2021
CrossTransformers: spatially-aware few-shot transfer
Carl Doersch
Ankush Gupta
Andrew Zisserman
ViT
212
330
0
22 Jul 2020
Deep Cosine Metric Learning for Person Re-Identification
N. Wojke
Alex Bewley
31
352
0
02 Dec 2018
Norm-Based Capacity Control in Neural Networks
Behnam Neyshabur
Ryota Tomioka
Nathan Srebro
119
577
0
27 Feb 2015
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