Connectionists: Call for Registration: Machine Learning Meets Scientific Understanding

[Schuster, Annika Noel]

The Emmy Noether group UDNN: Scientific Understanding and Deep Neural Networks is pleased to announce its upcoming workshop. This interdisciplinary event seeks to bring together philosophers of science and machine learning (ML), as well as ML practitioners, to explore the intersections between ML and scientific understanding.

Machine Learning Meets Scientific Understanding

June 26th and 27th, 2025

IBZ, TU Dortmund, Germany

Registration: https://forms.gle/H2weV4MUMnEEDQ679

Website: https://udnn.tu-dortmund.de/index.php/activities/workshop-machine-learning-meets-scientific-understanding/



Confirmed speakers and titles:

·       Cameron Buckner, Philosophy (University of Florida): Predictively-valid "Alien" Features, or Artifacts? Coping with Inscrutable Scientific Progress

·       Heather Champion, Philosophy (Tübingen University): On scientific discovery with machine learning: what is "strong" novelty?

·       Edward Chang, Computer Science (Stanford University): From Generative AI to AGI: Multi-LLM Agent Collaboration as a Path Forward

·       Finnur Dellsén, Philosophy (University of Iceland): Scientific Progress in the Age of AI

·       Henk W. de Regt, Philosophy (Radboud University) and Eugene Shalugin, Philosophy (Radboud University): Bridging Scientific Understanding and Creativity with an LLM Benchmark for Narrow-Domain Scientific Fields

·       Timo Freiesleben, Philosophy (Tübingen University): The Benchmarking Epistemology - What Inferences Can Scientists Draw from Competitive Comparisons of Prediction Models?

·       Giovanni Galli, Philosophy (University of Teramo): Deep-learning Models and Scientific Understanding through Explanations and Representations

·       Insa Lawler, Philosophy (UNC Greensboro): The Gradability of Explanatory Understanding

·       Holger Lyre, Philosophy (Magdeburg University): Semantic Grounding in Advanced LLMs

·       Daniel Neider, Computer Science (TU Dortmund University): A Gentle Introduction to Neural Network Verification (and How It Might Contribute to Evaluating Scientific Insights)

·       Sara Pernille Jensen, Philosophy (Oslo University): The Underdetermination of Representational Content in DNNs

·       Darrell P. Rowbottom, Philosophy (Lingnan University Hong Kong): What's Hidden Inside Predictively Successful Deep Learning Models?

·       Emily Sullivan, Philosophy (Utrecht University): Idealization Failure in ML

For inquiries, please contact the organizing committee at udnn.ht at tu-dortmund.de<mailto:udnn.ht at tu-dortmund.de>.

Main Organizers: Annika Schuster, Frauke Stoll, and Florian J. Boge



Wichtiger Hinweis: Die Information in dieser E-Mail ist vertraulich. Sie ist ausschließlich für den Adressaten bestimmt. Sollten Sie nicht der für diese E-Mail bestimmte Adressat sein, unterrichten Sie bitte den Absender und vernichten Sie diese Mail. Vielen Dank.
Unbeschadet der Korrespondenz per E-Mail, sind unsere Erklärungen ausschließlich final rechtsverbindlich, wenn sie in herkömmlicher Schriftform (mit eigenhändiger Unterschrift) oder durch Übermittlung eines solchen Schriftstücks per Telefax erfolgen.

Important note: The information included in this e-mail is confidential. It is solely intended for the recipient. If you are not the intended recipient of this e-mail please contact the sender and delete this message. Thank you. Without prejudice of e-mail correspondence, our statements are only legally binding when they are made in the conventional written form (with personal signature) or when such documents are sent by fax.
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.srv.cs.cmu.edu/pipermail/connectionists/attachments/20250604/b0519c7e/attachment.html>