Welcome!
Information Field Theory (IFT) is an information theory for fields and a probabilistic reasoning framework for continuous quantities. It is also a mathematical framework for deriving Bayesian image and signal reconstruction methods. IFT is closely related to Gaussian processes, generative neural operator networks, variational inference, statistical mechanics and quantum field theory, and has been shown to produce highly accurate results.
The WE Heraeus Information Field Theory 2026 (IFT-2026) conference brings together IFT theoreticians, practitioners, and interested newcomers to present and discuss their work, exchange experience, foster new collaborations, and establish new IFT-related research directions.
The key themes for IFT-2026 are:
- Mathematical foundations and insights into IFT
- IFT methods and algorithms
- Numerical Information Field Theory (NIFTy)
- Applications of IFT, including astrophysics, materials science and medical imaging
- The relation of IFT to AI methodologies, such as neural operator networks and diffusion models
- Inferring the states and laws governing dynamical systems
- The relation to other field theories (statistical, quantum, topological, etc.).
We invite you to the 1st Conference on Information Field Theory. It will take place from 23 to 27 November 2026 in Görlitz, Germany, and will be hosted by the German Center for Astrophysics (DZA).
The in-person workshop is by invitation only.
In case of high demand, a virtual component might be added later.
