On the Fairness of Disentangled Representations

31 May 2019

Francesco Locatello

Stefan Bauer

Olivier Bachem

Papers citing "On the Fairness of Disentangled Representations"

50 / 76 papers shown

Title
Fair Text Classification via Transferable Representations Thibaud Leteno Michael Perrot Charlotte Laclau Antoine Gourru Christophe Gravier FaML 88 0 0 10 Mar 2025
FairJob: A Real-World Dataset for Fairness in Online Systems Mariia Vladimirova Federico Pavone Eustache Diemert 47 1 0 03 Jul 2024
Improving Intervention Efficacy via Concept Realignment in Concept Bottleneck Models Nishad Singhi Jae Myung Kim Karsten Roth Zeynep Akata 50 1 0 02 May 2024
Bt-GAN: Generating Fair Synthetic Healthdata via Bias-transforming Generative Adversarial Networks R. Ramachandranpillai Md Fahim Sikder David Bergstrom Fredrik Heintz SyDa 38 6 0 21 Apr 2024
Towards Controllable Time Series Generation Yifan Bao Yihao Ang Qiang Huang Anthony K. H. Tung Zhiyong Huang DiffM 46 4 0 06 Mar 2024
Complexity Matters: Dynamics of Feature Learning in the Presence of Spurious Correlations GuanWen Qiu Da Kuang Surbhi Goel 32 8 0 05 Mar 2024
Revisiting Disentanglement in Downstream Tasks: A Study on Its Necessity for Abstract Visual Reasoning Ruiqian Nai Zixin Wen Ji Li Yuanzhi Li Yang Gao 46 2 0 01 Mar 2024
Towards a Unified Framework of Contrastive Learning for Disentangled Representations Stefan Matthes Zhiwei Han Hao Shen 37 4 0 08 Nov 2023
Compositional Generalization from First Principles Thaddäus Wiedemer Prasanna Mayilvahanan Matthias Bethge Wieland Brendel OCL 34 37 0 10 Jul 2023
Measuring Bias in AI Models: An Statistical Approach Introducing N-Sigma Daniel DeAlcala Ignacio Serna Aythami Morales Julian Fierrez J. Ortega-Garcia 26 6 0 26 Apr 2023
Beyond Accuracy: A Critical Review of Fairness in Machine Learning for Mobile and Wearable Computing Sofia Yfantidou Marios Constantinides Dimitris Spathis Athena Vakali Daniele Quercia F. Kawsar HAI FaML 28 18 0 27 Mar 2023
Fair Off-Policy Learning from Observational Data Dennis Frauen Valentyn Melnychuk Stefan Feuerriegel FaML OffRL 25 6 0 15 Mar 2023
Addressing Biases in the Texts using an End-to-End Pipeline Approach Shaina Raza Syed Raza Bashir Sneha Urooj Qamar 38 0 0 13 Mar 2023
Simple Disentanglement of Style and Content in Visual Representations Lilian Ngweta Subha Maity Alex Gittens Yuekai Sun Mikhail Yurochkin CoGe DRL 32 7 0 20 Feb 2023
SimFair: A Unified Framework for Fairness-Aware Multi-Label Classification Tianci Liu Haoyu Wang Yaqing Wang Xiaoqian Wang Lu Su Jing Gao 38 6 0 19 Feb 2023
eVAE: Evolutionary Variational Autoencoder Zhangkai Wu LongBing Cao Lei Qi BDL DRL 35 10 0 01 Jan 2023
ContraFeat: Contrasting Deep Features for Semantic Discovery Xinqi Zhu Chang Xu Dacheng Tao DRL 26 2 0 14 Dec 2022
Representational dissimilarity metric spaces for stochastic neural networks Lyndon Duong Jingyang Zhou Josue Nassar Jules Berman Jeroen Olieslagers Alex H. Williams 30 19 0 21 Nov 2022
Decomposing Counterfactual Explanations for Consequential Decision Making Martin Pawelczyk Lea Tiyavorabun Gjergji Kasneci CML 26 1 0 03 Nov 2022
Fair Visual Recognition via Intervention with Proxy Features Yi Zhang Jitao Sang Junyan Wang 23 1 0 02 Nov 2022
COFFEE: Counterfactual Fairness for Personalized Text Generation in Explainable Recommendation Nan Wang Qifan Wang Yi-Chia Wang Maziar Sanjabi Jingzhou Liu Hamed Firooz Hongning Wang Shaoliang Nie 28 6 0 14 Oct 2022
Disentanglement of Correlated Factors via Hausdorff Factorized Support Karsten Roth Mark Ibrahim Zeynep Akata Pascal Vincent Diane Bouchacourt CML OOD CoGe 41 33 0 13 Oct 2022
Fair Inference for Discrete Latent Variable Models Rashidul Islam Shimei Pan James R. Foulds FaML 46 1 0 15 Sep 2022
Gromov-Wasserstein Autoencoders Nao Nakagawa Ren Togo Takahiro Ogawa Miki Haseyama GAN DRL 26 11 0 15 Sep 2022
Fairness in Forecasting of Observations of Linear Dynamical Systems Quan Zhou Jakub Mareˇcek Robert Shorten AI4TS 45 5 0 12 Sep 2022
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 62 71 0 19 Jul 2022
Certifying Some Distributional Fairness with Subpopulation Decomposition Mintong Kang Linyi Li Maurice Weber Yang Liu Ce Zhang Bo-wen Li OOD 56 15 0 31 May 2022
Fair Representation Learning through Implicit Path Alignment Changjian Shui Qi Chen Jiaqi Li Boyu Wang Christian Gagné 43 28 0 26 May 2022
How do Variational Autoencoders Learn? Insights from Representational Similarity Lisa Bonheme M. Grzes CoGe SSL DRL 35 10 0 17 May 2022
Neural Contrastive Clustering: Fully Unsupervised Bias Reduction for Sentiment Classification Jared Mowery SSL 33 0 0 22 Apr 2022
Is Fairness Only Metric Deep? Evaluating and Addressing Subgroup Gaps in Deep Metric Learning Natalie Dullerud Karsten Roth Kimia Hamidieh Nicolas Papernot Marzyeh Ghassemi 37 15 0 23 Mar 2022
Robustness and Adaptation to Hidden Factors of Variation William Paul Philippe Burlina 29 0 0 03 Mar 2022
Bayes-Optimal Classifiers under Group Fairness Xianli Zeng Yan Sun Guang Cheng FaML 21 23 0 20 Feb 2022
Right for the Right Latent Factors: Debiasing Generative Models via Disentanglement Xiaoting Shao Karl Stelzner Kristian Kersting CML DRL 29 3 0 01 Feb 2022
Disentanglement and Generalization Under Correlation Shifts Christina M. Funke Paul Vicol Kuan-Chieh Jackson Wang Matthias Kümmerer R. Zemel Matthias Bethge OOD 39 7 0 29 Dec 2021
Latte: Cross-framework Python Package for Evaluation of Latent-Based Generative Models Alon Jacovi Junyoung Lee Alexander Lerch DRL 23 1 0 20 Dec 2021
On Fair Selection in the Presence of Implicit and Differential Variance V. Emelianov Nicolas Gast Krishna P. Gummadi P. Loiseau 32 21 0 10 Dec 2021
Latent Space Smoothing for Individually Fair Representations Momchil Peychev Anian Ruoss Mislav Balunović Maximilian Baader Martin Vechev FaML 36 19 0 26 Nov 2021
Modeling Techniques for Machine Learning Fairness: A Survey Mingyang Wan Daochen Zha Ninghao Liu Na Zou SyDa FaML 30 36 0 04 Nov 2021
Group-disentangled Representation Learning with Weakly-Supervised Regularization Linh-Tam Tran Amir Hosein Khasahmadi Aditya Sanghi Saeid Asgari Taghanaki DRL 34 1 0 23 Oct 2021
Identifiable Deep Generative Models via Sparse Decoding Gemma E. Moran Dhanya Sridhar Yixin Wang David M. Blei BDL 31 45 0 20 Oct 2021
EditVAE: Unsupervised Part-Aware Controllable 3D Point Cloud Shape Generation Shidi Li Miaomiao Liu Christian J. Walder 3DPC 54 28 0 13 Oct 2021
On the relationship between disentanglement and multi-task learning Lukasz Maziarka A. Nowak Maciej Wołczyk Andrzej Bedychaj OOD DRL 27 3 0 07 Oct 2021
Be More Active! Understanding the Differences between Mean and Sampled Representations of Variational Autoencoders Lisa Bonheme M. Grzes DRL 19 6 0 26 Sep 2021
Exploring the Latent Space of Autoencoders with Interventional Assays Felix Leeb Stefan Bauer M. Besserve Bernhard Schölkopf DRL 49 17 0 30 Jun 2021
Fair Normalizing Flows Mislav Balunović Anian Ruoss Martin Vechev AAML 19 36 0 10 Jun 2021
Fair Representations by Compression Xavier Gitiaux Huzefa Rangwala FaML 30 14 0 28 May 2021
Recovering Barabási-Albert Parameters of Graphs through Disentanglement Cristina Guzman Daphna Keidar Tristan Meynier Andreas Opedal Niklas Stoehr 19 0 0 03 May 2021
Discover the Unknown Biased Attribute of an Image Classifier Zhiheng Li Chenliang Xu 30 50 0 29 Apr 2021
Where and What? Examining Interpretable Disentangled Representations Xinqi Zhu Chang Xu Dacheng Tao FAtt DRL 56 38 0 07 Apr 2021