Main Track
Bayesian Neural Scaling Laws Extrapolation with Prior-Fitted Networks Inproceedings In: Proceedings of the 42nd International Conference on Machine Learning (ICML), 2025. |
FairPFN: A Tabular Foundation Model for Causal Fairness Inproceedings In: Proceedings of the 42nd International Conference on Machine Learning (ICML), 2025. |
Tuning LLM Judge Design Decisions for 1/1000 of the Cost Inproceedings In: Proceedings of the 42nd International Conference on Machine Learning (ICML), 2025. |
Position: The Future of Bayesian Prediction Is Prior-Fitted Inproceedings In: Proceedings of the 42nd International Conference on Machine Learning (ICML), 2025. |
Workshops
STRAND: Structure Refinement of RNA-Protein Complexes via Diffusion Inproceedings In: The 2nd workshop on Generative AI and Biology at ICML, 2025. |
Towards Synthetic Data for Fine-tuning Tabular Foundation Models Inproceedings In: Foundation Models for Structured Data workshop at ICML, 2025. |
Towards Benchmarking Foundation Models for Tabular Data With Text Inproceedings In: Foundation Models for Structured Data workshop at ICML, 2025. |
Real-TabPFN: Improving Tabular Foundation Models via Continued Pre-training With Real-World Data Inproceedings In: Foundation Models for Structured Data workshop at ICML, 2025. |
Early Stopping Tabular In-Context Learning Inproceedings In: Foundation Models for Structured Data workshop at ICML, 2025. |
Do-PFN: In-Context Learning for Causal Effect Estimation Inproceedings In: Foundation Models for Structured Data workshop at ICML, 2025. |