Evaluating Generative Models for Tabular Data: Novel Metrics and Benchmarking
Fuente:
arXiv
Saved in:
| Main Authors: | Herurkar, Dayananda, Ali, Ahmad, Dengel, Andreas |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Tabular Data Adapters: Improving Outlier Detection for Unlabeled Private Data
by: Herurkar, Dayananda, et al.
Published: (2025)
by: Herurkar, Dayananda, et al.
Published: (2025)
Fin-Fed-OD: Federated Outlier Detection on Financial Tabular Data
by: Herurkar, Dayananda, et al.
Published: (2024)
by: Herurkar, Dayananda, et al.
Published: (2024)
FedAD-Bench: A Unified Benchmark for Federated Unsupervised Anomaly Detection in Tabular Data
by: Anwar, Ahmed, et al.
Published: (2024)
by: Anwar, Ahmed, et al.
Published: (2024)
Evaluating Local Explainability Metrics for Machine Learning Models on Tabular Data
by: Pereira, Tomás, et al.
Published: (2026)
by: Pereira, Tomás, et al.
Published: (2026)
A Systematic Evaluation of Generative Models on Tabular Transportation Data
by: Wang, Chengen, et al.
Published: (2025)
by: Wang, Chengen, et al.
Published: (2025)
Tabular Data Generation Models: An In-Depth Survey and Performance Benchmarks with Extensive Tuning
by: Kindji, G. Charbel N., et al.
Published: (2024)
by: Kindji, G. Charbel N., et al.
Published: (2024)
TabSynDex: A Universal Metric for Robust Evaluation of Synthetic Tabular Data
by: Chundawat, Vikram S, et al.
Published: (2022)
by: Chundawat, Vikram S, et al.
Published: (2022)
Towards Benchmarking Foundation Models for Tabular Data With Text
by: Mráz, Martin, et al.
Published: (2025)
by: Mráz, Martin, et al.
Published: (2025)
From Private to Public: Benchmarking GANs in the Context of Private Time Series Classification
by: Mercier, Dominique, et al.
Published: (2023)
by: Mercier, Dominique, et al.
Published: (2023)
Risk In Context: Benchmarking Privacy Leakage of Foundation Models in Synthetic Tabular Data Generation
by: Byun, Jessup, et al.
Published: (2025)
by: Byun, Jessup, et al.
Published: (2025)
Transformers with Stochastic Competition for Tabular Data Modelling
by: Voskou, Andreas, et al.
Published: (2024)
by: Voskou, Andreas, et al.
Published: (2024)
On the Limits of Tabular Hardness Metrics for Deep RL: A Study with the Pharos Benchmark
by: Conserva, Michelangelo, et al.
Published: (2025)
by: Conserva, Michelangelo, et al.
Published: (2025)
Benchmarking Synthetic Tabular Data: A Multi-Dimensional Evaluation Framework
by: Sidorenko, Andrey, et al.
Published: (2025)
by: Sidorenko, Andrey, et al.
Published: (2025)
Data-Centric Machine Learning for Earth Observation: Necessary and Sufficient Features
by: Najjar, Hiba, et al.
Published: (2024)
by: Najjar, Hiba, et al.
Published: (2024)
Diffusion Models for Tabular Data Imputation and Synthetic Data Generation
by: Villaizán-Vallelado, Mario, et al.
Published: (2024)
by: Villaizán-Vallelado, Mario, et al.
Published: (2024)
Structured Evaluation of Synthetic Tabular Data
by: Yang, Scott Cheng-Hsin, et al.
Published: (2024)
by: Yang, Scott Cheng-Hsin, et al.
Published: (2024)
Benchmarking Federated Machine Unlearning methods for Tabular Data
by: Xiao, Chenguang, et al.
Published: (2025)
by: Xiao, Chenguang, et al.
Published: (2025)
Benchmarking Distribution Shift in Tabular Data with TableShift
by: Gardner, Josh, et al.
Published: (2023)
by: Gardner, Josh, et al.
Published: (2023)
Evaluating Inter-Column Logical Relationships in Synthetic Tabular Data Generation
by: Long, Yunbo, et al.
Published: (2025)
by: Long, Yunbo, et al.
Published: (2025)
Evaluating Synthetic Tabular Data Generated To Augment Small Sample Datasets
by: Marin, Javier
Published: (2022)
by: Marin, Javier
Published: (2022)
In the Search for Optimal Multi-view Learning Models for Crop Classification with Global Remote Sensing Data
by: Mena, Francisco, et al.
Published: (2024)
by: Mena, Francisco, et al.
Published: (2024)
What's Wrong with Your Synthetic Tabular Data? Using Explainable AI to Evaluate Generative Models
by: Kapar, Jan, et al.
Published: (2025)
by: Kapar, Jan, et al.
Published: (2025)
Can Multitask Learning Enhance Model Explainability?
by: Najjar, Hiba, et al.
Published: (2025)
by: Najjar, Hiba, et al.
Published: (2025)
A Novel Evaluation Metric for Unsupervised Learning in AIS-Based Maritime Anomaly Detection: MADQI
by: Gocer, Ismet, et al.
Published: (2026)
by: Gocer, Ismet, et al.
Published: (2026)
SHAP Distance: An Explainability-Aware Metric for Evaluating the Semantic Fidelity of Synthetic Tabular Data
by: Yu, Ke, et al.
Published: (2025)
by: Yu, Ke, et al.
Published: (2025)
TabularQGAN: A Quantum Generative Model for Tabular Data
by: Bhardwaj, Pallavi, et al.
Published: (2025)
by: Bhardwaj, Pallavi, et al.
Published: (2025)
Privacy-Preserving Tabular Synthetic Data Generation Using TabularARGN
by: Sidorenko, Andrey, et al.
Published: (2025)
by: Sidorenko, Andrey, et al.
Published: (2025)
A Practical Approach to Novel Class Discovery in Tabular Data
by: Troisemaine, Colin, et al.
Published: (2023)
by: Troisemaine, Colin, et al.
Published: (2023)
CTSyn: A Foundation Model for Cross Tabular Data Generation
by: Lin, Xiaofeng, et al.
Published: (2024)
by: Lin, Xiaofeng, et al.
Published: (2024)
How Well Does Your Tabular Generator Learn the Structure of Tabular Data?
by: Jiang, Xiangjian, et al.
Published: (2025)
by: Jiang, Xiangjian, et al.
Published: (2025)
Generating Counterfactual Trajectories with Latent Diffusion Models for Concept Discovery
by: Varshney, Payal, et al.
Published: (2024)
by: Varshney, Payal, et al.
Published: (2024)
Attention versus Contrastive Learning of Tabular Data -- A Data-centric Benchmarking
by: Rabbani, Shourav B., et al.
Published: (2024)
by: Rabbani, Shourav B., et al.
Published: (2024)
Quantifying Quality of Class-Conditional Generative Models in Time-Series Domain
by: Koochali, Alireza, et al.
Published: (2022)
by: Koochali, Alireza, et al.
Published: (2022)
Causal Representation Learning on High-Dimensional Data: Benchmarks, Reproducibility, and Evaluation Metrics
by: Sadeghi, Alireza, et al.
Published: (2026)
by: Sadeghi, Alireza, et al.
Published: (2026)
Hierarchical Conditional Tabular GAN for Multi-Tabular Synthetic Data Generation
by: Ågren, Wilhelm, et al.
Published: (2024)
by: Ågren, Wilhelm, et al.
Published: (2024)
FREQuency ATTribution: benchmarking frequency-based occlusion for time series data
by: Mercier, Dominique, et al.
Published: (2025)
by: Mercier, Dominique, et al.
Published: (2025)
TAEGAN: Generating Synthetic Tabular Data For Data Augmentation
by: Li, Jiayu, et al.
Published: (2024)
by: Li, Jiayu, et al.
Published: (2024)
CLIMB: Class-imbalanced Learning Benchmark on Tabular Data
by: Liu, Zhining, et al.
Published: (2025)
by: Liu, Zhining, et al.
Published: (2025)
AnoGAN for Tabular Data: A Novel Approach to Anomaly Detection
by: Singh, Aditya, et al.
Published: (2024)
by: Singh, Aditya, et al.
Published: (2024)
Generating Realistic Tabular Data with Large Language Models
by: Nguyen, Dang, et al.
Published: (2024)
by: Nguyen, Dang, et al.
Published: (2024)
Similar Items
-
Tabular Data Adapters: Improving Outlier Detection for Unlabeled Private Data
by: Herurkar, Dayananda, et al.
Published: (2025) -
Fin-Fed-OD: Federated Outlier Detection on Financial Tabular Data
by: Herurkar, Dayananda, et al.
Published: (2024) -
FedAD-Bench: A Unified Benchmark for Federated Unsupervised Anomaly Detection in Tabular Data
by: Anwar, Ahmed, et al.
Published: (2024) -
Evaluating Local Explainability Metrics for Machine Learning Models on Tabular Data
by: Pereira, Tomás, et al.
Published: (2026) -
A Systematic Evaluation of Generative Models on Tabular Transportation Data
by: Wang, Chengen, et al.
Published: (2025)