02.05.2025
Five Accepted Papers
28th International Conference on Artificial Intelligence and Statistics, Mai Khao, Thailand, May 03-05, 2025
We are happy to announce that MCML researchers have contributed a total of 5 papers to AISTATS 2025. Congrats to our researchers!
Main Track (5 papers)
Get rid of your constraints and reparametrize: A study in NNLS and implicit bias.
AISTATS 2025 - 28th International Conference on Artificial Intelligence and Statistics. Mai Khao, Thailand, May 03-05, 2025. URL
Paths and Ambient Spaces in Neural Loss Landscapes.
AISTATS 2025 - 28th International Conference on Artificial Intelligence and Statistics. Mai Khao, Thailand, May 03-05, 2025. URL
Incremental Uncertainty-aware Performance Monitoring with Active Labeling Intervention.
AISTATS 2025 - 28th International Conference on Artificial Intelligence and Statistics. Mai Khao, Thailand, May 03-05, 2025. URL
Solving Estimating Equations With Copulas.
AISTATS 2025 - 28th International Conference on Artificial Intelligence and Statistics. Mai Khao, Thailand, May 03-05, 2025. DOI
Additive Model Boosting: New Insights and Path(ologie)s.
AISTATS 2025 - 28th International Conference on Artificial Intelligence and Statistics. Mai Khao, Thailand, May 03-05, 2025. Oral Presentation. URL
Related
©Joachim Wendler - stock-adobe.com
02.01.2026
MCML Researchers in Highly-Ranked Journals
We are excited to announce that MCML researchers have three papers published in highly-ranked journals in %!s(
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.
16.12.2025
Fabian Theis Featured in Handelsblatt on the Future of AI in Precision Medicine
MCML PI Fabian Theis discusses AI-driven precision medicine and its growing impact on individualized healthcare and biomedical research.
16.12.2025
Gitta Kutyniok Featured in VDI Nachrichten on AI Ethics
Gitta Kutyniok discusses measurable criteria for ethical AI, promoting safe and responsible autonomous decision-making.
