ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2207.13865
  4. Cited By
Diversity Boosted Learning for Domain Generalization with Large Number
  of Domains

Diversity Boosted Learning for Domain Generalization with Large Number of Domains

28 July 2022
Xinlin Leng
Xiaoying Tang
Yatao Bian
    AI4CE
    OOD
ArXivPDFHTML

Papers citing "Diversity Boosted Learning for Domain Generalization with Large Number of Domains"

12 / 12 papers shown
Title
DrugOOD: Out-of-Distribution (OOD) Dataset Curator and Benchmark for
  AI-aided Drug Discovery -- A Focus on Affinity Prediction Problems with Noise
  Annotations
DrugOOD: Out-of-Distribution (OOD) Dataset Curator and Benchmark for AI-aided Drug Discovery -- A Focus on Affinity Prediction Problems with Noise Annotations
Yuanfeng Ji
Lu Zhang
Jiaxiang Wu
Bing Wu
Long-Kai Huang
...
Ping Luo
Shuigeng Zhou
Junzhou Huang
Peilin Zhao
Yatao Bian
OOD
110
73
0
24 Jan 2022
DORO: Distributional and Outlier Robust Optimization
DORO: Distributional and Outlier Robust Optimization
Runtian Zhai
Chen Dan
J. Zico Kolter
Pradeep Ravikumar
33
60
0
11 Jun 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
151
1,198
0
02 Mar 2021
Empirical or Invariant Risk Minimization? A Sample Complexity
  Perspective
Empirical or Invariant Risk Minimization? A Sample Complexity Perspective
Kartik Ahuja
Jun Wang
Amit Dhurandhar
Karthikeyan Shanmugam
Kush R. Varshney
OOD
59
79
0
30 Oct 2020
Learning Causal Models Online
Learning Causal Models Online
Khurram Javed
Martha White
Yoshua Bengio
CML
23
33
0
12 Jun 2020
Open Graph Benchmark: Datasets for Machine Learning on Graphs
Open Graph Benchmark: Datasets for Machine Learning on Graphs
Weihua Hu
Matthias Fey
Marinka Zitnik
Yuxiao Dong
Hongyu Ren
Bowen Liu
Michele Catasta
J. Leskovec
173
2,687
0
02 May 2020
Distributionally Robust Neural Networks for Group Shifts: On the
  Importance of Regularization for Worst-Case Generalization
Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization
Shiori Sagawa
Pang Wei Koh
Tatsunori B. Hashimoto
Percy Liang
OOD
46
1,217
0
20 Nov 2019
CyCADA: Cycle-Consistent Adversarial Domain Adaptation
CyCADA: Cycle-Consistent Adversarial Domain Adaptation
Judy Hoffman
Eric Tzeng
Taesung Park
Jun-Yan Zhu
Phillip Isola
Kate Saenko
Alexei A. Efros
Trevor Darrell
102
2,985
0
08 Nov 2017
Statistics of Robust Optimization: A Generalized Empirical Likelihood
  Approach
Statistics of Robust Optimization: A Generalized Empirical Likelihood Approach
John C. Duchi
Peter Glynn
Hongseok Namkoong
88
321
0
11 Oct 2016
Domain-Adversarial Training of Neural Networks
Domain-Adversarial Training of Neural Networks
Yaroslav Ganin
E. Ustinova
Hana Ajakan
Pascal Germain
Hugo Larochelle
François Laviolette
M. Marchand
Victor Lempitsky
GAN
OOD
318
9,418
0
28 May 2015
Learning Transferable Features with Deep Adaptation Networks
Learning Transferable Features with Deep Adaptation Networks
Mingsheng Long
Yue Cao
Jianmin Wang
Michael I. Jordan
OOD
166
5,163
0
10 Feb 2015
Determinantal point processes for machine learning
Determinantal point processes for machine learning
Alex Kulesza
B. Taskar
211
1,130
0
25 Jul 2012
1