We invite contributions on all aspects of imprecise probabilities, a term encompassing a wide range of mathematical and statistical models that quantify uncertainty without the restriction of precise probabilities. Topics of interest include, but are not
limited to, sets of probability measures, partial preference orderings, game-theoretic probability, choice functions, interval probabilities, risk measures, nonlinear expectations, belief functions, and possibility theory.
As is tradition at ISIPTA, accepted contributions will be presented and discussed in two separate sessions. Presentations are short and plenary. Detailed explanations and discussions are face-to-face relying on whichever medium you prefer – but having
a poster is encouraged – so as to favour interaction among participants.
We accept two types of submissions:
full papers and
one-page abstracts. The submission deadlines are
February 2nd, 2025 for full papers and
April 27th, 2025 for one-page abstracts; additional important dates like notification
of paper acceptance will be communicated in due course. Submission is through the
EasyChair platform following the
instructions on the conference
website for formatting guidelines.
All contributions will be made available on the conference website. Papers will be published in the
Proceedings of Machine Learning Research, although authors have the option to opt out of publication.
Registration is free for non-tenured scholars with accepted submission, and € 200 for tenured faculty with accepted submission. The fee for scholars without accepted submission and industry participants is € 600. The registration fee includes lunch,
coffee breaks, social dinner, and participation in the social event. Registration is up to June 1st, 2025, but we encourage participants to register only after a final decision on their submission has been made.
We look forward to welcoming you to Bielefeld!
The ISIPTA 2025 Steering Committee
Jasper De Bock
Sébastien Destercke
Alexander Erreygers
Max Nendel
Frank Riedel
Matthias Troffaes