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Learning explanations that are hard to vary

Learning explanations that are hard to vary

1 September 2020
Giambattista Parascandolo
Alexander Neitz
Antonio Orvieto
Luigi Gresele
Bernhard Schölkopf
    FAtt
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Papers citing "Learning explanations that are hard to vary"

37 / 37 papers shown
Title
Learning Optimal Prompt Ensemble for Multi-source Visual Prompt Transfer
Learning Optimal Prompt Ensemble for Multi-source Visual Prompt Transfer
Enming Zhang
Liwen Cao
Yanru Wu
Zijie Zhao
Guan Wang
Yang Li
49
0
0
09 Apr 2025
Seeking Consistent Flat Minima for Better Domain Generalization via Refining Loss Landscapes
Seeking Consistent Flat Minima for Better Domain Generalization via Refining Loss Landscapes
Aodi Li
Liansheng Zhuang
Xiao Long
Minghong Yao
Shafei Wang
180
0
0
18 Dec 2024
Meta Curvature-Aware Minimization for Domain Generalization
Meta Curvature-Aware Minimization for Domain Generalization
Z. Chen
Yiwen Ye
Feilong Tang
Yongsheng Pan
Yong-quan Xia
BDL
191
1
0
16 Dec 2024
Invariant Correlation of Representation with Label: Enhancing Domain Generalization in Noisy Environments
Invariant Correlation of Representation with Label: Enhancing Domain Generalization in Noisy Environments
Gaojie Jin
Ronghui Mu
Xinping Yi
Xiaowei Huang
Lijun Zhang
67
0
0
01 Jul 2024
PhysMLE: Generalizable and Priors-Inclusive Multi-task Remote
  Physiological Measurement
PhysMLE: Generalizable and Priors-Inclusive Multi-task Remote Physiological Measurement
Jiyao Wang
Hao Lu
Ange Wang
Xiao Yang
Ying Chen
Dengbo He
Kaishun Wu
21
3
0
10 May 2024
Advancing Generalizable Remote Physiological Measurement through the Integration of Explicit and Implicit Prior Knowledge
Advancing Generalizable Remote Physiological Measurement through the Integration of Explicit and Implicit Prior Knowledge
Yuting Zhang
Haobo Lu
Xin Liu
Ying Chen
Kaishun Wu
32
4
0
11 Mar 2024
Domain Generalization in Computational Pathology: Survey and Guidelines
Domain Generalization in Computational Pathology: Survey and Guidelines
Mostafa Jahanifar
M. Raza
Kesi Xu
T. Vuong
R. Jewsbury
...
Neda Zamanitajeddin
Jin Tae Kwak
S. Raza
F. Minhas
Nasir M. Rajpoot
OOD
26
17
0
30 Oct 2023
Improving Generalization in Visual Reinforcement Learning via
  Conflict-aware Gradient Agreement Augmentation
Improving Generalization in Visual Reinforcement Learning via Conflict-aware Gradient Agreement Augmentation
Siao Liu
Zhaoyu Chen
Yang Liu
Yuzheng Wang
Dingkang Yang
...
Ziqing Zhou
Xie Yi
Wei Li
Wenqiang Zhang
Zhongxue Gan
33
22
0
02 Aug 2023
Neuron Structure Modeling for Generalizable Remote Physiological
  Measurement
Neuron Structure Modeling for Generalizable Remote Physiological Measurement
Hao Lu
Zitong Yu
Xuesong Niu
Yingke Chen
28
31
0
10 Mar 2023
Meta Generative Attack on Person Reidentification
Meta Generative Attack on Person Reidentification
M. I. A V Subramanyam
AAML
14
8
0
16 Jan 2023
FIXED: Frustratingly Easy Domain Generalization with Mixup
FIXED: Frustratingly Easy Domain Generalization with Mixup
Wang Lu
Jindong Wang
Han Yu
Lei Huang
Xiang Zhang
Yiqiang Chen
Xingxu Xie
26
6
0
07 Nov 2022
Learning Gradient-based Mixup towards Flatter Minima for Domain
  Generalization
Learning Gradient-based Mixup towards Flatter Minima for Domain Generalization
Danni Peng
Sinno Jialin Pan
29
2
0
29 Sep 2022
Fuse and Attend: Generalized Embedding Learning for Art and Sketches
Fuse and Attend: Generalized Embedding Learning for Art and Sketches
U. Dutta
29
0
0
20 Aug 2022
Domain-invariant Feature Exploration for Domain Generalization
Domain-invariant Feature Exploration for Domain Generalization
Wang Lu
Jindong Wang
Haoliang Li
Yiqiang Chen
Xing Xie
OOD
30
69
0
25 Jul 2022
Domain Generalization for Activity Recognition via Adaptive Feature
  Fusion
Domain Generalization for Activity Recognition via Adaptive Feature Fusion
Xin Qin
Jindong Wang
Yiqiang Chen
Wang Lu
Xinlong Jiang
OOD
36
35
0
21 Jul 2022
Assaying Out-Of-Distribution Generalization in Transfer Learning
Assaying Out-Of-Distribution Generalization in Transfer Learning
F. Wenzel
Andrea Dittadi
Peter V. Gehler
Carl-Johann Simon-Gabriel
Max Horn
...
Chris Russell
Thomas Brox
Bernt Schiele
Bernhard Schölkopf
Francesco Locatello
OOD
OODD
AAML
51
71
0
19 Jul 2022
The Importance of Background Information for Out of Distribution
  Generalization
The Importance of Background Information for Out of Distribution Generalization
Jupinder Parmar
Khaled Kamal Saab
Brian Pogatchnik
D. Rubin
Christopher Ré
OOD
16
0
0
17 Jun 2022
The Two Dimensions of Worst-case Training and the Integrated Effect for
  Out-of-domain Generalization
The Two Dimensions of Worst-case Training and the Integrated Effect for Out-of-domain Generalization
Zeyi Huang
Haohan Wang
Dong Huang
Yong Jae Lee
Eric P. Xing
11
22
0
09 Apr 2022
Invariance Learning based on Label Hierarchy
Invariance Learning based on Label Hierarchy
S. Toyota
Kenji Fukumizu
OOD
19
1
0
29 Mar 2022
Fortuitous Forgetting in Connectionist Networks
Fortuitous Forgetting in Connectionist Networks
Hattie Zhou
Ankit Vani
Hugo Larochelle
Aaron Courville
CLL
6
42
0
01 Feb 2022
Local Learning Matters: Rethinking Data Heterogeneity in Federated
  Learning
Local Learning Matters: Rethinking Data Heterogeneity in Federated Learning
Matías Mendieta
Taojiannan Yang
Pu Wang
Minwoo Lee
Zhengming Ding
C. L. P. Chen
FedML
19
158
0
28 Nov 2021
Discovery of New Multi-Level Features for Domain Generalization via
  Knowledge Corruption
Discovery of New Multi-Level Features for Domain Generalization via Knowledge Corruption
A. Frikha
Denis Krompass
Volker Tresp
OOD
32
1
0
09 Sep 2021
Fishr: Invariant Gradient Variances for Out-of-Distribution
  Generalization
Fishr: Invariant Gradient Variances for Out-of-Distribution Generalization
Alexandre Ramé
Corentin Dancette
Matthieu Cord
OOD
38
204
0
07 Sep 2021
Domain Generalization via Gradient Surgery
Domain Generalization via Gradient Surgery
Lucas Mansilla
Rodrigo Echeveste
Diego H. Milone
Enzo Ferrante
OOD
16
78
0
03 Aug 2021
Pointer Value Retrieval: A new benchmark for understanding the limits of
  neural network generalization
Pointer Value Retrieval: A new benchmark for understanding the limits of neural network generalization
Chiyuan Zhang
M. Raghu
Jon M. Kleinberg
Samy Bengio
OOD
21
30
0
27 Jul 2021
An Information-theoretic Approach to Distribution Shifts
An Information-theoretic Approach to Distribution Shifts
Marco Federici
Ryota Tomioka
Patrick Forré
OOD
29
17
0
07 Jun 2021
OoD-Bench: Quantifying and Understanding Two Dimensions of
  Out-of-Distribution Generalization
OoD-Bench: Quantifying and Understanding Two Dimensions of Out-of-Distribution Generalization
Nanyang Ye
Kaican Li
Haoyue Bai
Runpeng Yu
Lanqing Hong
Fengwei Zhou
Zhenguo Li
Jun Zhu
CML
OOD
37
106
0
07 Jun 2021
Can Subnetwork Structure be the Key to Out-of-Distribution
  Generalization?
Can Subnetwork Structure be the Key to Out-of-Distribution Generalization?
Dinghuai Zhang
Kartik Ahuja
Yilun Xu
Yisen Wang
Aaron Courville
OOD
20
95
0
05 Jun 2021
SAND-mask: An Enhanced Gradient Masking Strategy for the Discovery of
  Invariances in Domain Generalization
SAND-mask: An Enhanced Gradient Masking Strategy for the Discovery of Invariances in Domain Generalization
Soroosh Shahtalebi
Jean-Christophe Gagnon-Audet
Touraj Laleh
Mojtaba Faramarzi
Kartik Ahuja
Irina Rish
20
59
0
04 Jun 2021
Evading the Simplicity Bias: Training a Diverse Set of Models Discovers
  Solutions with Superior OOD Generalization
Evading the Simplicity Bias: Training a Diverse Set of Models Discovers Solutions with Superior OOD Generalization
Damien Teney
Ehsan Abbasnejad
Simon Lucey
A. Hengel
23
86
0
12 May 2021
Generalizing to Unseen Domains: A Survey on Domain Generalization
Generalizing to Unseen Domains: A Survey on Domain Generalization
Jindong Wang
Cuiling Lan
Chang-Shu Liu
Yidong Ouyang
Tao Qin
Wang Lu
Yiqiang Chen
Wenjun Zeng
Philip S. Yu
OOD
54
1,169
0
02 Mar 2021
Model-Invariant State Abstractions for Model-Based Reinforcement
  Learning
Model-Invariant State Abstractions for Model-Based Reinforcement Learning
Manan Tomar
Amy Zhang
Roberto Calandra
Matthew E. Taylor
Joelle Pineau
19
24
0
19 Feb 2021
Therapeutics Data Commons: Machine Learning Datasets and Tasks for Drug
  Discovery and Development
Therapeutics Data Commons: Machine Learning Datasets and Tasks for Drug Discovery and Development
Kexin Huang
Tianfan Fu
Wenhao Gao
Yue Zhao
Yusuf Roohani
J. Leskovec
Connor W. Coley
Cao Xiao
Jimeng Sun
Marinka Zitnik
OOD
LM&MA
27
261
0
18 Feb 2021
Gradient Starvation: A Learning Proclivity in Neural Networks
Gradient Starvation: A Learning Proclivity in Neural Networks
Mohammad Pezeshki
Sekouba Kaba
Yoshua Bengio
Aaron Courville
Doina Precup
Guillaume Lajoie
MLT
45
257
0
18 Nov 2020
When is invariance useful in an Out-of-Distribution Generalization
  problem ?
When is invariance useful in an Out-of-Distribution Generalization problem ?
Masanori Koyama
Shoichiro Yamaguchi
OOD
31
65
0
04 Aug 2020
What shapes feature representations? Exploring datasets, architectures,
  and training
What shapes feature representations? Exploring datasets, architectures, and training
Katherine L. Hermann
Andrew Kyle Lampinen
OOD
23
153
0
22 Jun 2020
Out-of-Distribution Generalization via Risk Extrapolation (REx)
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
215
901
0
02 Mar 2020
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