The second Workshop on “Machine Learning Meets Differential Equations: From Theory to Applications” (ML-DE), co-located with ECAI 2025, is set to explore the synergies between Machine Learning (ML) and Differential Equations (DE), highlighting how these fields can collaborate to enhance prediction accuracies and advance explainable AI. This event will focus on integrating DEs into ML architectures and applying ML to solve complex DE problems, aiming to foster innovations in fields ranging from physics to biology. With a commitment to sustainable AI practices, the workshop is dedicated to developing energy-efficient algorithms and reducing the computational footprint of ML, encouraging a community-driven approach to pushing the boundaries of research and application at the intersection of ML and DE.

This concise description encapsulates the workshop’s objectives, themes, and the potential impact on various scientific and technological domains, positioning it as a pivotal meeting point for researchers and practitioners interested in the future of intelligent technologies.

Please find a detailed description of the workshop here. Also have a look at last year’s workshop to get an impression of the workshop.

Important Dates

• Submission Deadline: 15th of June 2025 23:59 CEST 10th of July 2025 23:59 CEST
• Notification of Acceptance: 15th of July 2025 latest by 15th of August 2025
• Workshop Date: 26th of October, Full day
• Review Transfer Option Deadline: 20th of July 2025 23:59 CEST

Highlights of Call for Papers

Explore the core of our Call for Papers for the ML-DE Workshop, dedicated to the convergence of Machine Learning and Differential Equations. For detailed submission guidelines and topics of interest, ensure to visit our Call for Papers page.

Brief Submission Guidelines

• Paper Format: Submissions must be formatted according to the PMLR LaTeX template. Either use our prefilled version on overleaf or the offical PMLR Template and change according to our Example
• Length: Up to 8 pages, excluding references and appendices.
• Blind Review: Submissions should be anonymized to adhere to our double-blind review process.
• Submission Link: https://easychair.org/conferences/?conf=mlde2025
• Review Transfer Option: For papers not accepted in the ECAI main track, authors can submit to our workshop. Please follow the rules from the main conference regarding “RESUBMISSION FROM OTHER CONFERENCES” that can be found here. Please use this format when submitting your paper. For questions contact us at MLDEWorkshopECAI25@hsu-hh.de.

Snapshot of Topics of Interest

We invite submissions that bridge Machine Learning with Differential Equations, covering a spectrum from theoretical innovations to practical applications. For a full exploration of the themes and how to submit, visit the full Call for Papers.

Engage with us in advancing this interdisciplinary nexus!