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Stochastic Numerics and Statistical Learning Workshop 2025

May 18-25, 2025
Auditorium 0215 between Buildings 2 and 3

We are excited to announce the upcoming Stochastic Numerics and Statistical Learning: Theory and Applications Workshop 2025.

Following the highly successful last three years’ editions, this year’s workshop promises to be another engaging and insightful event for researchers, faculty members, and students interested in stochastic algorithms, statistical learning, optimization, and approximation.

The 2025 workshop aims to build on the achievements of last year’s event, which attracted over 150 participants from various universities and research institutes. In previous years, attendees had the opportunity to learn from through insightful talks, interactive mini-courses, and vibrant poster sessions.

This year, the workshop will once again showcase contributions that offer mathematical foundations for algorithmic analysis or highlight relevant applications. Confirmed speakers include renowned experts from institutions such as KTH, École Polytechnique, Heidelberg University, EPFL, Paris-Saclay Université, RWTH Aachen, TU Berlin, Delft University, Oxford University, CUHK Shenzhen and Imperial College London, among others.

The 2025 workshop will feature:

  • Engaging talks and presentations by leading experts in the field.
  • Two poster sessions on May 18 and 19 (Building 9 session), providing an opportunity for participants to present their research.

We encourage researchers, faculty members, and students from all disciplines to attend this workshop to broaden their understanding of stochastic numerics and statistical learning. Participants will have the opportunity to network with experts, explore potential applications, and foster collaborations across various research areas.

For more information about the event, including confirmed speakers and schedules, please visit the following link.

We look forward to your participation in this exciting workshop and hope to see many of you there, either in person or remotely.

Prof. Raul Tempone (Chair)

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