MITHIC 2026 | Multivariate Information Theory and High-Order Interactions in Complex Systems

General Information

The behaviour of complex systems often arises from intricate interactions between multiple components, not merely pairwise but higher-order interactions. Traditional analysis tools are limited in detecting such complex dependencies. Multivariate Information Theory (MVIT) offers a robust framework to capture and quantify these interactions, providing tools such as Total Correlation, O-Information, and Partial Information Decomposition.

This workshop aims to bring together early-career researchers, students, and domain experts to explore MVIT, both from theoretical and practical perspectives. Thematic focus areas include applications in a range of complex systems — covering neuroscience, epidemics, and systems biology — with special attention to the overlap between MVIT and high-order network theory. By blending instruction with collaborative exploration, the MITHIC workshop seeks to advance understanding of how to use multivariate dependencies to study collective behaviour emerging from high-order interactions and to foster new interdisciplinary research directions.

Are you working with high-dimensional datasets? Curious about how complex, emergent behaviour arises from interactions among many variables? Join us for MITHIC 2026, a hands-on workshop exploring how Multivariate Information Theory (MVIT) can help you uncover hidden structures and high-order dependencies in Complex Systems. Learn the theoretical and practical tools for analysing interactions beyond the pairwise level, focusing on collective dynamics. We will explore key MVIT metrics like Total Correlation, O-Information, and Partial Information Decomposition, and their applications across disciplines.

Important Dates

• Application opens: 1 December, 2025
• Application EXTENDED deadline: 13 February, 2026
• Notification of acceptance: 16 March, 2026
• Workshop dates: 11-13 May 2026

Application

We welcome graduate students, postdocs, and researchers in physics, biology, neuroscience, AI, data science, and related fields. Prior programming experience in Python is helpful but not mandatory. The workshop is free of charge, thus limited to a maximal number of 30 participants. These will be selected based on the quality of their applications. To apply, please use the online application form.

We will provide lunch and a coffee break each day. Also, we invite you to a social dinner to complete the event, free of charge. However, we do not cover travel or accommodation expenses.

Student Grants

We also provide a limited number of student grants to help cover travel or accommodation expenses of young scholars with limited or no access to financial resources. Applicants wishing to be considered for a travel grant should indicate this in their application form and provide a brief motivation. Successful applicants will be notified along with their acceptance letters.

Venue

The conference will be held at Institute for Bio-computation and Physics of Complex Systems (BIFI). Address: Mariano Esquillor, Edificio I + D, Campus Río Ebro, Calle María de Luna, 1, 50018 Zaragoza, Spain

Program

The afternoons will be dedicated to interactive, hands-on tutorials using Python-based MVIT toolkits. Participants will learn to apply metrics such as Total Correlation, Multivariate Mutual Information, and O-Information to synthetic and real datasets. Each group will be encouraged to explore a research question through guided project work, culminating in short presentations. Participants will be grouped and supported through prepared Jupyter notebooks and curated datasets. Optionally, they may bring their own data.

Topics include

• Theory and practice of MVIT metrics
• Real-world examples in neuroscience, epidemics, and finance
• Connections to High-Order Network Theory and Topological Data Analysis

What to Expect?

• Expert lecture on MVIT and complex systems
• Python-based tutorials for MVIT analysis
• Group work on participant-defined research questions
• Collaborative roundtables linking MVIT to broader theories

Source and more details: https://mithic2026.github.io/