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WILDS: A Benchmark of in-the-Wild Distribution Shifts

WILDS: A Benchmark of in-the-Wild Distribution Shifts

14 December 2020
Pang Wei Koh
Shiori Sagawa
Henrik Marklund
Sang Michael Xie
Marvin Zhang
Akshay Balsubramani
Weihua Hu
Michihiro Yasunaga
Richard Lanas Phillips
Irena Gao
Tony Lee
Etiene David
Ian Stavness
Wei Guo
Berton A. Earnshaw
I. Haque
Sara Beery
J. Leskovec
A. Kundaje
Emma Pierson
Sergey Levine
Chelsea Finn
Percy Liang
    OOD
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Papers citing "WILDS: A Benchmark of in-the-Wild Distribution Shifts"

32 / 232 papers shown
Title
Network Generalization Prediction for Safety Critical Tasks in Novel
  Operating Domains
Network Generalization Prediction for Safety Critical Tasks in Novel Operating Domains
Molly O'Brien
Michael Medoff
Julia V. Bukowski
Gregory Hager
OOD
13
3
0
17 Aug 2021
Managing ML Pipelines: Feature Stores and the Coming Wave of Embedding
  Ecosystems
Managing ML Pipelines: Feature Stores and the Coming Wave of Embedding Ecosystems
Laurel J. Orr
Atindriyo Sanyal
Xiao Ling
Karan Goel
Megan Leszczynski
13
18
0
11 Aug 2021
Sequential Multivariate Change Detection with Calibrated and Memoryless
  False Detection Rates
Sequential Multivariate Change Detection with Calibrated and Memoryless False Detection Rates
Oliver Cobb
A. V. Looveren
Janis Klaise
21
6
0
02 Aug 2021
Did the Model Change? Efficiently Assessing Machine Learning API Shifts
Did the Model Change? Efficiently Assessing Machine Learning API Shifts
Lingjiao Chen
Tracy Cai
Matei A. Zaharia
James Y. Zou
18
17
0
29 Jul 2021
MultiBench: Multiscale Benchmarks for Multimodal Representation Learning
MultiBench: Multiscale Benchmarks for Multimodal Representation Learning
Paul Pu Liang
Yiwei Lyu
Xiang Fan
Zetian Wu
Yun Cheng
...
Peter Wu
Michelle A. Lee
Yuke Zhu
Ruslan Salakhutdinov
Louis-Philippe Morency
VLM
21
157
0
15 Jul 2021
The Evolution of Out-of-Distribution Robustness Throughout Fine-Tuning
The Evolution of Out-of-Distribution Robustness Throughout Fine-Tuning
Anders Andreassen
Yasaman Bahri
Behnam Neyshabur
Rebecca Roelofs
OOD
OODD
22
78
0
30 Jun 2021
Detecting Errors and Estimating Accuracy on Unlabeled Data with
  Self-training Ensembles
Detecting Errors and Estimating Accuracy on Unlabeled Data with Self-training Ensembles
Jiefeng Chen
Frederick Liu
Besim Avci
Xi Wu
Yingyu Liang
S. Jha
19
60
0
29 Jun 2021
Laplace Redux -- Effortless Bayesian Deep Learning
Laplace Redux -- Effortless Bayesian Deep Learning
Erik A. Daxberger
Agustinus Kristiadi
Alexander Immer
Runa Eschenhagen
Matthias Bauer
Philipp Hennig
BDL
UQCV
31
288
0
28 Jun 2021
Examining and Combating Spurious Features under Distribution Shift
Examining and Combating Spurious Features under Distribution Shift
Chunting Zhou
Xuezhe Ma
Paul Michel
Graham Neubig
OOD
19
64
0
14 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
27
105
0
07 Jun 2021
Quantifying and Improving Transferability in Domain Generalization
Quantifying and Improving Transferability in Domain Generalization
Guojun Zhang
Han Zhao
Yaoliang Yu
Pascal Poupart
35
37
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
18
95
0
05 Jun 2021
Privacy-Preserving Constrained Domain Generalization via Gradient
  Alignment
Privacy-Preserving Constrained Domain Generalization via Gradient Alignment
Chris Xing Tian
Haoliang Li
Yufei Wang
Shiqi Wang
13
4
0
14 May 2021
The iWildCam 2021 Competition Dataset
The iWildCam 2021 Competition Dataset
Sara Beery
Arush Agarwal
Elijah Cole
Vighnesh Birodkar
22
75
0
07 May 2021
Size-Invariant Graph Representations for Graph Classification
  Extrapolations
Size-Invariant Graph Representations for Graph Classification Extrapolations
Beatrice Bevilacqua
Yangze Zhou
Bruno Ribeiro
OOD
31
108
0
08 Mar 2021
Domain Generalization: A Survey
Domain Generalization: A Survey
Kaiyang Zhou
Ziwei Liu
Yu Qiao
Tao Xiang
Chen Change Loy
OOD
AI4CE
21
979
0
03 Mar 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
52
1,168
0
02 Mar 2021
Two Sides of Meta-Learning Evaluation: In vs. Out of Distribution
Two Sides of Meta-Learning Evaluation: In vs. Out of Distribution
Amrith Rajagopal Setlur
Oscar Li
Virginia Smith
30
13
0
23 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
25
259
0
18 Feb 2021
In-N-Out: Pre-Training and Self-Training using Auxiliary Information for
  Out-of-Distribution Robustness
In-N-Out: Pre-Training and Self-Training using Auxiliary Information for Out-of-Distribution Robustness
Sang Michael Xie
Ananya Kumar
Robbie Jones
Fereshte Khani
Tengyu Ma
Percy Liang
OOD
153
62
0
08 Dec 2020
The Open Catalyst 2020 (OC20) Dataset and Community Challenges
The Open Catalyst 2020 (OC20) Dataset and Community Challenges
L. Chanussot
Abhishek Das
Siddharth Goyal
Thibaut Lavril
Muhammed Shuaibi
...
Brandon M. Wood
Junwoong Yoon
Devi Parikh
C. L. Zitnick
Zachary W. Ulissi
221
498
0
20 Oct 2020
RobustBench: a standardized adversarial robustness benchmark
RobustBench: a standardized adversarial robustness benchmark
Francesco Croce
Maksym Andriushchenko
Vikash Sehwag
Edoardo Debenedetti
Nicolas Flammarion
M. Chiang
Prateek Mittal
Matthias Hein
VLM
217
674
0
19 Oct 2020
An Investigation of Why Overparameterization Exacerbates Spurious
  Correlations
An Investigation of Why Overparameterization Exacerbates Spurious Correlations
Shiori Sagawa
Aditi Raghunathan
Pang Wei Koh
Percy Liang
144
369
0
09 May 2020
Machine learning on DNA-encoded libraries: A new paradigm for
  hit-finding
Machine learning on DNA-encoded libraries: A new paradigm for hit-finding
Kevin McCloskey
E. Sigel
S. Kearnes
L. Xue
Xia Tian
...
C. Hupp
Anthony D. Keefe
Christopher J. Mulhern
Ying Zhang
Patrick F. Riley
41
102
0
31 Jan 2020
A Survey on Bias and Fairness in Machine Learning
A Survey on Bias and Fairness in Machine Learning
Ninareh Mehrabi
Fred Morstatter
N. Saxena
Kristina Lerman
Aram Galstyan
SyDa
FaML
294
4,187
0
23 Aug 2019
Are We Modeling the Task or the Annotator? An Investigation of Annotator
  Bias in Natural Language Understanding Datasets
Are We Modeling the Task or the Annotator? An Investigation of Annotator Bias in Natural Language Understanding Datasets
Mor Geva
Yoav Goldberg
Jonathan Berant
235
319
0
21 Aug 2019
VoxCeleb2: Deep Speaker Recognition
VoxCeleb2: Deep Speaker Recognition
Joon Son Chung
Arsha Nagrani
Andrew Zisserman
214
2,224
0
14 Jun 2018
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language
  Understanding
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding
Alex Jinpeng Wang
Amanpreet Singh
Julian Michael
Felix Hill
Omer Levy
Samuel R. Bowman
ELM
294
6,943
0
20 Apr 2018
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
268
5,652
0
05 Dec 2016
Dialogue Learning With Human-In-The-Loop
Dialogue Learning With Human-In-The-Loop
Jiwei Li
Alexander H. Miller
S. Chopra
MarcÁurelio Ranzato
Jason Weston
OffRL
216
134
0
29 Nov 2016
CAD2RL: Real Single-Image Flight without a Single Real Image
CAD2RL: Real Single-Image Flight without a Single Real Image
Fereshteh Sadeghi
Sergey Levine
SSL
216
809
0
13 Nov 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
247
9,109
0
06 Jun 2015
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