Erstwhile current (that is, past) affairs
Nov 2024. I give a talk for the LMU
research colloquium in ethics of AI.
Oct 2024. My
paper "Statistical learning theory and Occam's razor: The core argument" has been accepted for publication in
Minds and Machines.
Oct 2024. Sara Jensen (supervised by Karen Crowther and myself) visits us from Oslo for the semester. Welcome, Sara!
Oct 2024. In the 2024-25 winter semester I teach an advanced seminar on
Epistemology and Theory of Machine Learning. I also organize, together with
Timo Freiesleben, a new round of the
MCMP reading group on philosophy of machine learning.
Oct 2024. Katia Parshina starts as a PhD student in my project. Welcome, Katia!
Sep 2024. I join the Konrad Zuse School of Excellence in Reliable AI (
relAI).
Jul 2024. We organize the MCMP
Summer School for Widening Participation in Mathematical Philosophy.
Jun 2024. I give an invited talk at
The Age of Algorithms workshop in Bucharest.
May 2024. I speak at the
Machine Learning under Weakly Structured Information workshop at the LMU Department of Statistics, and at the
Generalization and Overfitting workshop at the HLRS in Stuttgart.
Apr 2024. In the 2024 summer semester I organize, together with
Timo Freiesleben, a new round of the
MCMP reading group on philosophy of machine learning.
Apr 2024. I give an invited talk in the
Séminaire général de l'IHPST, Paris 1 Panthéon-Sorbonne University, and a submitted talk at the
ML, Explain Yourself! conference in Utrecht.
Mar 2024. I speak at the MCMP interdisciplinary
Workshop on Modelling Complex Systems in climate science.
Feb 2024. I give an invited talk at the
Epistemological Issues of Machine Learning in Science workshop in Dortmund.
Jan 2024. I give an invited talk in the
Computational Health Seminar at Helmholtz Munich. I serve as program committee member for
ACM FAccT'24.
Dec 2023. I give an invited (online) talk for the
Jowett Society of the University of Oxford. An updated version is also available of my paper on "
Statistical learning theory and Occam's razor."
Nov 2023. I give an invited talk at a symposium in Utrecht on
Philosophy of Science, AI and Machine Learning organised by the Dutch Association for Philosophy of Science (NVWF).
Oct 2023. In the 2023-24 winter semester I teach an advanced seminar on
Philosophical Aspects of Deep Learning. I also organize, together with
Timo Freiesleben, a new round of the
MCMP reading group on philosophy of machine learning.
Sep 2023.
Philosophy & Technology accepts my
invited commentary of David Watson's "
On the philosophy of unsupervised learning."
Sep 2023. I give an invited talk at
PhilML'23 in Tübingen.
Aug 2023. I give a talk at
ECAP 9 in Vienna and at
Progic 2023 in Utrecht.
Jul 2023. I teach a session at the
Trust and Machine Learning summer school of the High-Performance Computing Center Stuttgart.
Jun 2023.
Philosophy of Science accepts my
invited review of John Norton's
The Material Theory of Induction. A first version is also available of my paper on "
Statistical learning theory and Occam's razor."
Jun 2023. I co-organize the
Machine Learning meets Mathematical Philosophy workshop with the MCMP and the
Munich Center for Machine Learning. I also give an invited talk at the
AI & Mathematics (AIM2023) workshop at the University of Twente.
May 2023. I represent Munich at the Tübingen-Hannover Workshop on Philosophy of AI/ML. I also give a talk at the Formal Methods cluster of the King's College London
Department of Philosophy.
Apr 2023. In the 2023 summer semester I teach an advanced seminar on
Philosophy of Statistics. I also organize, together with
Timo Freiesleben, a new round of the
MCMP reading group on philosophy of machine learning.
Apr 2023. My
paper with Peter Grünwald on the no-free-lunch theorems is featured on
te.ma (in German).
Apr 2023. I start my Emmy Noether project.
Mar 2023. I visit Jan-Willem Romeijn at the Groningen Department of Theoretical Philosophy.
Mar 2023. I organize a workshop on
Theory and Epistemology of Machine Learning.
Feb 2023. I visit Konstantin Genin at the Tübingen Cluster of Excellence "Machine Learning for Science".
