01.05.2024
Six Accepted Papers
27th International Conference on Artificial Intelligence and Statistics, Valencia, Spain, May 02-04, 2024
We are happy to announce that MCML researchers have contributed a total of 6 papers to AISTATS 2024. Congrats to our researchers!
Main Track (6 papers)
Identifying Copeland Winners in Dueling Bandits with Indifferences.
AISTATS 2024 - 27th International Conference on Artificial Intelligence and Statistics. Valencia, Spain, May 02-04, 2024. URL
Bayesian Semi-structured Subspace Inference.
AISTATS 2024 - 27th International Conference on Artificial Intelligence and Statistics. Valencia, Spain, May 02-04, 2024. URL
SVARM-IQ: Efficient Approximation of Any-order Shapley Interactions through Stratification.
AISTATS 2024 - 27th International Conference on Artificial Intelligence and Statistics. Valencia, Spain, May 02-04, 2024. URL
An Online Bootstrap for Time Series.
AISTATS 2024 - 27th International Conference on Artificial Intelligence and Statistics. Valencia, Spain, May 02-04, 2024. URL
Scalable Higher-Order Tensor Product Spline Models.
AISTATS 2024 - 27th International Conference on Artificial Intelligence and Statistics. Valencia, Spain, May 02-04, 2024. URL
Enhancing Hypergradients Estimation: A Study of Preconditioning and Reparameterization.
AISTATS 2024 - 27th International Conference on Artificial Intelligence and Statistics. Valencia, Spain, May 02-04, 2024. URL GitHub
Related
15.01.2026
Blind Matching – Aligning Images and Text Without Training or Labels
CVPR 2025 research from Daniel Cremers’ group shows how images and text can be aligned without training data, labels, or paired examples.
08.01.2026
High-Res Images, Less Wait: A Simple Flow for Image Generation
ECCV 2024 research led by Björn Ommer’s team enables faster high-resolution image generation by boosting diffusion models with flow matching.
©Joachim Wendler - stock-adobe.com
02.01.2026
MCML Researchers in Highly-Ranked Journals
We are excited to announce that MCML researchers have four papers published in highly-ranked journals in 2026.
18.12.2025
"See, Don’t Assume": Revealing and Reducing Gender Bias in AI
ICLR 2025 research led by Zeynep Akata’s team reveals and reduces gender bias in popular vision-language AI models.