Mathematical Foundations of AI

Chalmers @ Room KSC - 8-10 June 2026

Applications are open. Click here to register! Deadline: 15/05

"Is AI doomed to become an engineering-only field, or is it possible to build a science of AI?"

The workshop will explore the following topics:

• Transformers: these architectures are at the core of Large Language Models and are rapidly revolutionising all fields of ML.  Despite theoretical efforts, approaches remain scattered, and we lack a unifying framework. This theme aims to unify these perspectives on how to study transformers.

• Diffusion Models/Flow Matching: these models are the state of the art for generative tasks. Theoretical progress in this field is proceeding at an unprecedented pace, making results from just one or two years ago obsolete. The goal is to assess the current state of research and describe the open questions that lie ahead.

• Associative Memories: models of associative memory have recently returned as a core topic in AI research, given their analogies with aspects of learning and memorization in Transformers and Diffusion Models. In this theme, we aim to reconcile classical and recent results to repurpose them to understand these modern technologies.

Invited talks

Program

The program will be announced shortly. 

Organisers

Sponsor