Boris van Breugel
12 papers · 2021–2025 · 6 venues · across top CS/AI venues
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Achievements
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π£ Hot Topic Early Bird π Conference Polyglot Β· Silver π Interdisciplinary Bridge Β· Bronze πΊοΈ Taxonomy Completionist (24) π€ Dynamic Duo (10)
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The Questioner
(3)
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Keyword Collector
(55)
π
Trend Setter
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Century Club Β· Bronze
π₯
Unstoppable Β· Bronze
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Research topics
Machine Learning
(9)
Artificial Intelligence
(6)
Deep Learning
(6)
Application Areas
(5)
Core AI
(5)
Models
(5)
Optimization & Theory
(4)
Architectures
(2)
Learning Types Β· Machine Learning
(2)
Natural Language Processing
(1)
Security & Privacy
(1)
Bayesian & Probabilistic
(1)
Generation
(1)
Learning Paradigms
(1)
Learning Types Β· Deep Learning
(1)
Keywords
generative model
(4)
uncertainty quantification
(2)
tabular data
(2)
synthetic data
(2)
density estimation
(2)
model evaluation
(1)
data augmentation
(1)
privacy attack
(1)
overfitting detection
(1)
posterior approximation
(1)
diffusion model
(1)
bias mitigation
(1)
distribution shift
(1)
out-of-distribution detection
(1)
downstream task
(1)
generative adversarial network
(1)
structural causal model
(1)
synthetic data generation
(1)
generative modeling
(1)
causal inference
(1)
Papers
Position: All Current Generative Fidelity and Diversity Metrics are Flawed
ICML 2025
Curated LLM: Synergy of LLMs and Data Curation for tabular augmentation in low-data regimes
ICML 2024
Position: Why Tabular Foundation Models Should Be a Research Priority
ICML 2024
RadEdit: stress-testing biomedical vision models via diffusion image editing
ECCV 2024
Soft Mixture Denoising: Beyond the Expressive Bottleneck of Diffusion Models
ICLR 2024
Can You Rely on Your Model Evaluation? Improving Model Evaluation with Synthetic Test Data
NeurIPS 2023
Membership Inference Attacks against Synthetic Data through Overfitting Detection
AISTATS 2023
Synthetic Data, Real Errors: How (Not) to Publish and Use Synthetic Data
ICML 2023
What is Flagged in Uncertainty Quantification? Latent Density Models for Uncertainty Categorization
NeurIPS 2023
How Faithful is your Synthetic Data? Sample-level Metrics for Evaluating and Auditing Generative Models
ICML 2022
DECAF: Generating Fair Synthetic Data Using Causally-Aware Generative Networks
NeurIPS 2021
Stereotype and Skew: Quantifying Gender Bias in Pre-trained and Fine-tuned Language Models
EACL 2021