Spuriosity Didn't Kill the Classifier: Using Invariant Predictions to
Harness Spurious Features

Spuriosity Didn't Kill the Classifier: Using Invariant Predictions to Harness Spurious Features

19 July 2023

Andrei Liviu Nicolicioiu

Marin Vlastelica

Julius von Kügelgen

Bernhard Schölkopf

Papers citing "Spuriosity Didn't Kill the Classifier: Using Invariant Predictions to Harness Spurious Features"

18 / 18 papers shown

Title
Invariance Pair-Guided Learning: Enhancing Robustness in Neural Networks Martin Surner Abdelmajid Khelil Ludwig Bothmann OOD 53 0 0 26 Feb 2025
Scalable Out-of-distribution Robustness in the Presence of Unobserved Confounders Parjanya Prashant Seyedeh Baharan Khatami Bruno Ribeiro Babak Salimi 74 0 0 29 Nov 2024
Adapting to Shifting Correlations with Unlabeled Data Calibration Minh Le Nguyen Alan Q. Wang Heejong Kim Mert R. Sabuncu OOD 18 1 0 09 Sep 2024
Spurious Correlations in Concept Drift: Can Explanatory Interaction Help? Cristiana Lalletti Stefano Teso 27 1 0 23 Jul 2024
Unifying Invariant and Variant Features for Graph Out-of-Distribution via Probability of Necessity and Sufficiency Xuexin Chen Ruichu Cai Kaitao Zheng Zhifan Jiang Zhengting Huang Zhifeng Hao Zijian Li 54 0 0 21 Jul 2024
Accuracy on the wrong line: On the pitfalls of noisy data for out-of-distribution generalisation Amartya Sanyal Yaxi Hu Yaodong Yu Yian Ma Yixin Wang Bernhard Schölkopf OODD 45 1 0 27 Jun 2024
Domain Generalisation via Imprecise Learning Anurag Singh Siu Lun Chau S. Bouabid Krikamol Muandet AI4CE OOD 38 5 0 06 Apr 2024
Spurious Correlations in Machine Learning: A Survey Wenqian Ye Guangtao Zheng Xu Cao Yunsheng Ma Aidong Zhang OOD AAML CML 39 33 0 20 Feb 2024
Unifying Invariance and Spuriousity for Graph Out-of-Distribution via Probability of Necessity and Sufficiency Xuexin Chen Ruichu Cai Kaitao Zheng Zhifan Jiang Zhengting Huang Zhifeng Hao Zijian Li 24 2 0 14 Feb 2024
On Provable Length and Compositional Generalization Kartik Ahuja Amin Mansouri OODD 38 7 0 07 Feb 2024
When Graph Neural Network Meets Causality: Opportunities, Methodologies and An Outlook Wenzhao Jiang Hao Liu Hui Xiong CML AI4CE 44 2 0 19 Dec 2023
Discovering environments with XRM Mohammad Pezeshki Diane Bouchacourt Mark Ibrahim Jimuyang Zhang Pascal Vincent David Lopez-Paz 43 18 0 28 Sep 2023
Nonparametric Identifiability of Causal Representations from Unknown Interventions Julius von Kügelgen M. Besserve Wendong Liang Luigi Gresele Armin Kekić Elias Bareinboim David M. Blei Bernhard Schölkopf CML 18 56 0 01 Jun 2023
Invariant and Transportable Representations for Anti-Causal Domain Shifts Yibo Jiang Victor Veitch OOD 123 32 0 04 Jul 2022
If your data distribution shifts, use self-learning E. Rusak Steffen Schneider George Pachitariu L. Eck Peter V. Gehler Oliver Bringmann Wieland Brendel Matthias Bethge VLM OOD TTA 77 29 0 27 Apr 2021
Gradient Matching for Domain Generalization Yuge Shi Jeffrey S. Seely Philip H. S. Torr Siddharth Narayanaswamy Awni Y. Hannun Nicolas Usunier Gabriel Synnaeve OOD 213 246 0 20 Apr 2021
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
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 317 11,681 0 09 Mar 2017