Boris van Breugel

According to our database1, Boris van Breugel authored at least 17 papers between 2021 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
LaTable: Towards Large Tabular Models.
CoRR, 2024

Why Tabular Foundation Models Should Be a Research Priority.
CoRR, 2024

Curated LLM: Synergy of LLMs and Data Curation for tabular augmentation in low-data regimes.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Position: Why Tabular Foundation Models Should Be a Research Priority.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Soft Mixture Denoising: Beyond the Expressive Bottleneck of Diffusion Models.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
RadEdit: stress-testing biomedical vision models via diffusion image editing.
CoRR, 2023

Curated LLM: Synergy of LLMs and Data Curation for tabular augmentation in ultra low-data regimes.
CoRR, 2023

Beyond Privacy: Navigating the Opportunities and Challenges of Synthetic Data.
CoRR, 2023

What is Flagged in Uncertainty Quantification? Latent Density Models for Uncertainty Categorization.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Can You Rely on Your Model Evaluation? Improving Model Evaluation with Synthetic Test Data.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Synthetic Data, Real Errors: How (Not) to Publish and Use Synthetic Data.
Proceedings of the International Conference on Machine Learning, 2023

Membership Inference Attacks against Synthetic Data through Overfitting Detection.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022
Practical Approaches for Fair Learning with Multitype and Multivariate Sensitive Attributes.
CoRR, 2022

DAUX: a Density-based Approach for Uncertainty eXplanations.
CoRR, 2022

How Faithful is your Synthetic Data? Sample-level Metrics for Evaluating and Auditing Generative Models.
Proceedings of the International Conference on Machine Learning, 2022

2021
DECAF: Generating Fair Synthetic Data Using Causally-Aware Generative Networks.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Stereotype and Skew: Quantifying Gender Bias in Pre-trained and Fine-tuned Language Models.
Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, 2021


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