Prof. Alexei A. Efros from UC Berkeley will speak on the topic ”We are (still?) not giving data enough credit“ as part of the Munich AI Lectures on Wednesday, July 17, 2024, at 6.30 pm in the…
[read more]
Stefanie Rinderle-Ma is going to talk about how generative AI, especially Large Language Models, can enhance business process modeling and discovery by enabling domain experts to create and refine…
[read more]
What does the future of Artificial Intelligence (AI) look like and what are new developments in research? Outstanding national and international AI scientists and decision-makers from politics,…
[read more]
This short course covers recent developments in graphical and causal modeling in Statistics/Machine Learning. It is comprised of the following three lectures, each two hours long.
[read more]
What should we think about before AI does it for us? MDSI core member Prof. Enkelejda Kasneci, MDSI advisory board member Prof. Alena Buyx and other experts focus on the topic of AI and its impacts at…
[read more]
Be inspired, network and become active yourself. The Sustainability Day is for all interested: students, staff, professors and external guests. Only together can we shape the sustainable development…
[read more]
On 15-17 May 2024, "simulation-based inference" (SBI) or "likelihood-free inference" (LFI) methods will be discussed during PHYSTAT 2024. The event will be streamed live. It is supported by the…
[read more]
On May 13, MDSI is hosting the Munich Kaggle Meetup. Kaggle is a platform for data science competitions, where you can improve your skills and compete with others to solve real-world problems. Whether…
[read more]
This is the fourth workshop dedicated to GraphNeT – A deep learning library for neutrino telescopes. The goal is to bring together researchers working at the intersection of neutrino telescope…
[read more]
We are pleased to announce the workshop Getting Started with Microsoft Azure for Bioinformatics. The workshop will cover success stories, a practical session (e.g. for deep learning), and best…
[read more]
