| IWR School on Machine Learning for Fundamental Physics
Machine Learning is here to stay and is shaping the future of fundamental physics research. From optimal inference, over theory-inspired network architectures, to anomaly detection, representation learning and foundation models, a new generation of scientists is driving these exciting developments. This school aims to further strengthen technical expertise and foster new connections.
The 2025 IWR School on Machine Learning for Fundamental Physics is aimed at advanced PhD students specializing in scientific machine learning. We particularly encourage registrations from researchers with experience in scientific machine learning, as demonstrated by papers or preprints related to the topic of the school. The school takes place at the Interdisciplinary Center for Scientific Computing (IWR) at Heidelberg University September 15th-19th 2025. | Organizers:
Scientific: Tilman Plehn, David Shih, Caroline Heneka
At IWR: Jan Keese, Anne Leonhardt, Michael Winckler | IWR, Mathematikon, Im Neuenheimer Feld 205, 69120 Heidelberg | |
| International Marsilius Academy:
„AI and Human Values: Exploring technological, social, and normative perspectives“
About the event:
The rapid development of generative AI is having a profound impact on modern society. At the same time, it raises critical questions about the underlying values and the ethical, legal, and societal implications of these technologies. The aim of the Summer School is to critically examine the normative foundations of generative AI and to discuss which values are embedded in its design and how these values can be reflected upon and modeled. The Summer School offers an interdisciplinary space to connect perspectives from computer science, linguistics, philosophy, theology, medicine, and law. It is aimed at early-career researchers who seek to engage in meaningful discourse on values and norms in AI development and wish to build lasting scholarly networks.
Application deadline: June 27, 2025 | Organisation:
Marsilius-Kolleg und Heidelberg Center for Digital Humanities
Wissenschaftliches Komitee:
Maria Becker (Computerlinguistik),
Michael Boutros (Genomforschung),
Michael Gertz (Informatik),
Nora Heinzelmann (Philosophie),
Friederike Nüssel (Theologie) | Marsilius Kolleg, Heidelberg
INF130.1 | |
| Generative Models in Science and Machine Learning
Generative models are powerful tools with growing impact across a wide range of scientific and technological domains. They enable the learning of complex distributions and the incorporation of prior knowledge, uncertainty, and structure into data-driven models. While deep learning plays a central role in many recent advances, the workshop also welcomes contributions based on alternative methodologies. We aim to bring together researchers working at the intersection of generative modeling, statistical learning theory, Bayesian inference, machine learning, and scientific computing. Topics include the mathematical foundations and statistical guarantees of generative models, algorithmic innovations for training and sampling, and applications for scientific and real-world problems. The workshop's goal is to foster exchange between the statistics, machine learning, and applied mathematics communities, and to identify promising directions for future research. | Jakob Zech
Claudia Strauch | Internationales Wissenschaftsforum Heidelberg,
Hauptstraße 242, 69117 Heidelberg. | |
