Interpretability of Machine Learning on Experimental Data | Kristina Braverman скачать в хорошем качестве

Interpretability of Machine Learning on Experimental Data | Kristina Braverman

Recorded on 02/05/2026 Watch the recording without ads at https://www.nitmb.org/curiosity-and-c... Title: Interpretability of Machine Learning on Experimental Data Speaker: Kristina Braverman This talk was recorded as part of the 'Curiosity-Driven Dialogue and Collaboration Between Experiment and Theory' workshop Workshop Overview: An inherent challenge of interdisciplinary research is breaching the barriers between theory and experiment, both in communication across disciplines and expertise in the domain-specific fundamentals. As such, it is not always obvious when there is the potential for collaboration, or how theorists and experimentalists can best navigate their collaborations to address open problems and inspire new research. In collaboration, curiosity is as fundamental as it is to science broadly – experimentalists and theorists have the power to inspire each other when they are receptive and curious to learn perspectives and techniques outside their respective fields. Interdisciplinary discussion and research can yield novel biological questions, uncover general principles, and reveal unexplored avenues by which theory can advance our understanding of biological systems. This workshop will bring together early-career researchers across disciplines with the goal of inspiring curiosity and revealing avenues of collaboration. Sessions will be aimed at encouraging learning across the experiment-theory spectrum and stimulating cross-disciplinary conversation, with a mix of tutorial-style talks, presentations from leaders at the scientific intersection, and discussion sessions. NITMB Overview: The NSF-Simons National Institute for Theory and Mathematics in Biology (NITMB) aims to integrate the disciplines of mathematics and biology in order to transform the practice of biological research and to inspire new mathematical discoveries. NITMB is a partnership between Northwestern University and the University of Chicago. It is funded by the National Science Foundation DMS-2235451 and the Simons Foundations MP-TMPS-00005320. The mission of the NITMB is to create a nationwide collaborative research community that will generate new mathematical results and uncover the “rules of life” through theories, data-informed mathematical models, and computational and statistical tools.