Learning in Networks Reading Group and Seminar Series: Tuesdays, 12pm in 330 Gross Hall; lunch included The institute focuses on fundamental questions in statistical inference, machine learning, causal inference, and optimization on networks, with particular emphasis on statistical-computational tradeoffs, message-passing algorithms, learning dynamics, and network-based market design. By fostering collaboration across disciplines, the institute aims […]
Organized by the SWS in STEM and Staff of the Rhodes Information Initiative. With support from the Office of Faculty Advancement, we continue our mission of promoting fellowship and scientific connection among women scientists at Duke at ALL career stagesand across scientific disciplines. Half-hour, broad-audience lectures are paired with a delicious catered lunch and time […]
Please RSVP here: https://duke.kualibuild.com/app/6a6a085327a10f029e5f0530/start The goal of the Justice in AI PopUp Institute is to bring together disparate groups on campus whose work is relevant to justice in AI and learn from each other as well was from outside visitors. It is organized by Walter Sinnott-Armstrong (Duke Philosophy) and Brandon L. Garrett (Duke Law). Dates: […]
Learning in Networks Reading Group and Seminar Series: Tuesdays, 12pm in 330 Gross Hall; lunch included The institute focuses on fundamental questions in statistical inference, machine learning, causal inference, and optimization on networks, with particular emphasis on statistical-computational tradeoffs, message-passing algorithms, learning dynamics, and network-based market design. By fostering collaboration across disciplines, the institute aims […]
Sponsored by the Rhodes Information Initiative, the Humanistic AI conference is designed to foster substantive dialogue between the humanities and the sciences. The conference will explore questions such as: How might large language models be used to simulate or operationalize historical knowledge? How is generative AI reshaping concepts such as authorship, interpretation, and evidence? And […]
A Duke Math major, Chris Finger earned a PhD in Applied and Computational Mathematics from Princeton. After moving to risk management at JP Morgan, he was a founding partner of Risk metrics, where he held roles including Head of Research, Head of Credit Products, and head of the Geneva Branch Office. He then spent 12 […]
Learning in Networks Reading Group and Seminar Series: Tuesdays, 12pm in 330 Gross Hall; lunch included The institute focuses on fundamental questions in statistical inference, machine learning, causal inference, and optimization on networks, with particular emphasis on statistical-computational tradeoffs, message-passing algorithms, learning dynamics, and network-based market design. By fostering collaboration across disciplines, the institute aims […]
Learning in Networks Reading Group and Seminar Series: Tuesdays, 12pm in 330 Gross Hall; lunch included The institute focuses on fundamental questions in statistical inference, machine learning, causal inference, and optimization on networks, with particular emphasis on statistical-computational tradeoffs, message-passing algorithms, learning dynamics, and network-based market design. By fostering collaboration across disciplines, the institute aims […]
Learning in Networks Reading Group and Seminar Series: Tuesdays, 12pm in 330 Gross Hall; lunch included The institute focuses on fundamental questions in statistical inference, machine learning, causal inference, and optimization on networks, with particular emphasis on statistical-computational tradeoffs, message-passing algorithms, learning dynamics, and network-based market design. By fostering collaboration across disciplines, the institute aims […]
Hosted by Duke AI Health and the Pratt School of Engineering and the Digital Health Innovation at Duke University, this event will bring together experts from healthcare, engineering, industry, and academia to explore how AI can drive health innovation. Duke's strengths in AI product development and healthcare innovation will be leveraged to explore responsible AI […]
Learning in Networks Reading Group and Seminar Series: Tuesdays, 12pm in 330 Gross Hall; lunch included The institute focuses on fundamental questions in statistical inference, machine learning, causal inference, and optimization on networks, with particular emphasis on statistical-computational tradeoffs, message-passing algorithms, learning dynamics, and network-based market design. By fostering collaboration across disciplines, the institute aims […]
Classes resume (8:30 AM)
