Adversarial Robustness of VAEs across Intersectional Subgroups
Fuente:
arXiv
Saved in:
| Main Authors: | Ramanaik, Chethan Krishnamurthy, Roy, Arjun, Ntoutsi, Eirini |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
GRILL: Restoring Gradient Signal in Ill-Conditioned Layers for More Effective Adversarial Attacks on Autoencoders
by: Ramanaik, Chethan Krishnamurthy, et al.
Published: (2025)
by: Ramanaik, Chethan Krishnamurthy, et al.
Published: (2025)
Synthetic Tabular Data Generation for Class Imbalance and Fairness: A Comparative Study
by: Panagiotou, Emmanouil, et al.
Published: (2024)
by: Panagiotou, Emmanouil, et al.
Published: (2024)
TABFAIRGDT: A Fast Fair Tabular Data Generator using Autoregressive Decision Trees
by: Panagiotou, Emmanouil, et al.
Published: (2025)
by: Panagiotou, Emmanouil, et al.
Published: (2025)
TABCF: Counterfactual Explanations for Tabular Data Using a Transformer-Based VAE
by: Panagiotou, Emmanouil, et al.
Published: (2024)
by: Panagiotou, Emmanouil, et al.
Published: (2024)
Explanations as Bias Detectors: A Critical Study of Local Post-hoc XAI Methods for Fairness Exploration
by: Papanikou, Vasiliki, et al.
Published: (2025)
by: Papanikou, Vasiliki, et al.
Published: (2025)
Towards Cohesion-Fairness Harmony: Contrastive Regularization in Individual Fair Graph Clustering
by: Ghodsi, Siamak, et al.
Published: (2024)
by: Ghodsi, Siamak, et al.
Published: (2024)
Exploring Fusion Techniques in Multimodal AI-Based Recruitment: Insights from FairCVdb
by: Swati, Swati, et al.
Published: (2024)
by: Swati, Swati, et al.
Published: (2024)
A Deep Latent Factor Graph Clustering with Fairness-Utility Trade-off Perspective
by: Ghodsi, Siamak, et al.
Published: (2025)
by: Ghodsi, Siamak, et al.
Published: (2025)
MMM-fair: An Interactive Toolkit for Exploring and Operationalizing Multi-Fairness Trade-offs
by: Swati, Swati, et al.
Published: (2025)
by: Swati, Swati, et al.
Published: (2025)
FairBranch: Mitigating Bias Transfer in Fair Multi-task Learning
by: Roy, Arjun, et al.
Published: (2023)
by: Roy, Arjun, et al.
Published: (2023)
Adversarial robustness of VAEs through the lens of local geometry
by: Khan, Asif, et al.
Published: (2022)
by: Khan, Asif, et al.
Published: (2022)
Subgroups Matter for Robust Bias Mitigation
by: Alloula, Anissa, et al.
Published: (2025)
by: Alloula, Anissa, et al.
Published: (2025)
TopoPrune: Robust Data Pruning via Unified Latent Space Topology
by: Roy, Arjun, et al.
Published: (2026)
by: Roy, Arjun, et al.
Published: (2026)
Unity by Diversity: Improved Representation Learning in Multimodal VAEs
by: Sutter, Thomas M., et al.
Published: (2024)
by: Sutter, Thomas M., et al.
Published: (2024)
Disentangling Granularity: An Implicit Inductive Bias in Factorized VAEs
by: Chen, Zihao, et al.
Published: (2025)
by: Chen, Zihao, et al.
Published: (2025)
MESD: A Risk-Sensitive Metric for Explanation Fairness Across Intersectional Subgroups
by: Popoola, Gideon, et al.
Published: (2026)
by: Popoola, Gideon, et al.
Published: (2026)
A Testable Certificate for Constant Collapse in Teacher-Guided VAEs
by: Zhang, Zegu, et al.
Published: (2026)
by: Zhang, Zegu, et al.
Published: (2026)
Learning Energy-based Variational Latent Prior for VAEs
by: Dutta, Debottam, et al.
Published: (2025)
by: Dutta, Debottam, et al.
Published: (2025)
Enhancing Unimodal Latent Representations in Multimodal VAEs through Iterative Amortized Inference
by: Oshima, Yuta, et al.
Published: (2024)
by: Oshima, Yuta, et al.
Published: (2024)
Adaptive-lambda Subtracted Importance Sampled Scores in Machine Unlearning for DDPMs and VAEs
by: Dini, MohammadParsa, et al.
Published: (2025)
by: Dini, MohammadParsa, et al.
Published: (2025)
Multiple Invertible and Partial-Equivariant Function for Latent Vector Transformation to Enhance Disentanglement in VAEs
by: Jung, Hee-Jun, et al.
Published: (2025)
by: Jung, Hee-Jun, et al.
Published: (2025)
Graph2TS: Structure-Controlled Time Series Generation via Quantile-Graph VAEs
by: Du, Shaoshuai, et al.
Published: (2026)
by: Du, Shaoshuai, et al.
Published: (2026)
Achieving Hilbert-Schmidt Independence Under Rényi Differential Privacy for Fair and Private Data Generation
by: Hyrup, Tobias, et al.
Published: (2025)
by: Hyrup, Tobias, et al.
Published: (2025)
Adversarially Robust Decision Transformer
by: Tang, Xiaohang, et al.
Published: (2024)
by: Tang, Xiaohang, et al.
Published: (2024)
Adversarial Examples Might be Avoidable: The Role of Data Concentration in Adversarial Robustness
by: Pal, Ambar, et al.
Published: (2023)
by: Pal, Ambar, et al.
Published: (2023)
How Worst-Case Are Adversarial Attacks? Linking Adversarial and Perturbation Robustness
by: Rossolini, Giulio
Published: (2026)
by: Rossolini, Giulio
Published: (2026)
Maintaining Adversarial Robustness in Continuous Learning
by: Ru, Xiaolei, et al.
Published: (2024)
by: Ru, Xiaolei, et al.
Published: (2024)
Robust Decision Aggregation with Adversarial Experts
by: Guo, Yongkang, et al.
Published: (2024)
by: Guo, Yongkang, et al.
Published: (2024)
Adversarial Robustness Overestimation and Instability in TRADES
by: Li, Jonathan Weiping, et al.
Published: (2024)
by: Li, Jonathan Weiping, et al.
Published: (2024)
Adversarial Diffusion for Robust Reinforcement Learning
by: Foffano, Daniele, et al.
Published: (2025)
by: Foffano, Daniele, et al.
Published: (2025)
Algorithms for Adversarially Robust Deep Learning
by: Robey, Alexander
Published: (2025)
by: Robey, Alexander
Published: (2025)
Bridging Symmetry and Robustness: On the Role of Equivariance in Enhancing Adversarial Robustness
by: Wang, Longwei, et al.
Published: (2025)
by: Wang, Longwei, et al.
Published: (2025)
Bias Detection via Maximum Subgroup Discrepancy
by: Němeček, Jiří, et al.
Published: (2025)
by: Němeček, Jiří, et al.
Published: (2025)
Adversarial Preference Learning for Robust LLM Alignment
by: Wang, Yuanfu, et al.
Published: (2025)
by: Wang, Yuanfu, et al.
Published: (2025)
CEAR: Certified Ensemble Adversarial Robustness in DNNs
by: Sadig, Daniel, et al.
Published: (2026)
by: Sadig, Daniel, et al.
Published: (2026)
ROKA: Robust Knowledge Unlearning against Adversaries
by: Shin, Jinmyeong, et al.
Published: (2026)
by: Shin, Jinmyeong, et al.
Published: (2026)
Towards Adversarially Robust Deep Metric Learning
by: Ke, Xiaopeng
Published: (2025)
by: Ke, Xiaopeng
Published: (2025)
ProxiMix: Enhancing Fairness with Proximity Samples in Subgroups
by: Hu, Jingyu, et al.
Published: (2024)
by: Hu, Jingyu, et al.
Published: (2024)
Representation Invariance and Allocation: When Subgroup Balance Matters
by: Alloula, Anissa, et al.
Published: (2025)
by: Alloula, Anissa, et al.
Published: (2025)
Exploring Adversarial Robustness of Deep State Space Models
by: Qi, Biqing, et al.
Published: (2024)
by: Qi, Biqing, et al.
Published: (2024)
Similar Items
-
GRILL: Restoring Gradient Signal in Ill-Conditioned Layers for More Effective Adversarial Attacks on Autoencoders
by: Ramanaik, Chethan Krishnamurthy, et al.
Published: (2025) -
Synthetic Tabular Data Generation for Class Imbalance and Fairness: A Comparative Study
by: Panagiotou, Emmanouil, et al.
Published: (2024) -
TABFAIRGDT: A Fast Fair Tabular Data Generator using Autoregressive Decision Trees
by: Panagiotou, Emmanouil, et al.
Published: (2025) -
TABCF: Counterfactual Explanations for Tabular Data Using a Transformer-Based VAE
by: Panagiotou, Emmanouil, et al.
Published: (2024) -
Explanations as Bias Detectors: A Critical Study of Local Post-hoc XAI Methods for Fairness Exploration
by: Papanikou, Vasiliki, et al.
Published: (2025)