2023 Lecture on Information Theory & Information Field TheoryScript Recordings Handouts Exercises Examinations
Signal inference requires intelligent methods to obtain high fidelity signal recovery from noisy, incomplete data. The theoretical and mathematical framework in which methods for signal reconstruction, imaging, data analysis, and machine learning are derived should be information theory to which these lectures will introduce first (first 1/3 semester 17.04.2023-19.05.20223, suited for Bachelor and Master students, 3 ETCS). Based on this, information theory for fields will be developed, which can be used to reconstruct signals over continuous from data (remaining 2/3 semester, 22.05.2023-21.07.2023 more targeted at Master students, 6 ETCS).
The following topics will be addressed:
- Aristotelian & Bayesian logic
- Measurement process
- Information measures
- Relation to thermodynamics and statistical mechanics
- Theory of Wiener filter
- Construction of optimal non-linear filters for signal reconstruction
The course will be a in person blackboard lecture. Recordings of previous courses can be found here. Please note that the blackboard lecture might deviate from those and will be the one that defines the material to be covered by exercises and examinations.
There will be two lectures/discussion sessions per week
Information theory, begin: 17.04.2023, end: 19.05.2023
Information field theory, begin: 22.05.2023, end: 21.07.2023
- Monday, 14:00 - 16:00, Geschw.-Scholl-Platz 1, Großer Physik-HS (N 120)
- Tuesday, 14:00 - 16:00, Theresienstr. 37, A348
Information theory: Monday June 5th, 14:00 - 16:00, Geschw.-Scholl-Platz 1, Großer Physik-HS (N 120)
Information field theory: Tuesday July 18th, 14:00 - 16:00, Theresienstr. 37, A348
2023 Tutorials for Information Theory & Information Field Theory
There are three tutorials per week: Begin: 19.04.2022, End: 20.07.2022
- group A, IT and IFT, Wednesday 18:00 - 20:00, Theresienstr. 37 / A 449 ,
- group B, only IT, Thursday, 10:00 - 12:00, Theresienstr. 37 / A 249 ,
- group C, IT and IFT, Thursday, 16:00 - 18:00, Theresienstr. 37 / A 449
Exercises are optional, but can be used to get bonus points for the exam. The bonus will be 15% of the points which are necessary to achieve a 1.0 in the exam. It will be ensured that top marks are well reachable without the bonus. The bonus system is structured as following:
- Each week we will hand out work sheets with approximately three problems. To each task and subtask, respectively points are assigned.
- Prior to each tutorial students are asked to give note which problems they are able to present. There will be a list at the beginning of each tutorial.
- In order to get the full bonus for the respective exam (IT or IFT), Students need to sign up for at least 60% of all possible achievable points during each part, IT and IFT.
- The tutors choose students randomly from the list mentioned earlier.
- In case the student is not able to properly solve the task, instead of getting the points for this exercise the student will receive up to twice the negative number of points he could have gained by the correct solution.
- EXTRA: If you want to present voluntarily and do a exceptionally clear and
instructive presentation you might get double as many points. If the presentation is not very clear,
you only get the regular amount of points
(Talk to the tutor before the beginning of the tutorial)
Signal reconstruction with Python, EDV-Zusatzausbildung (SQ1+SQ2, September 2023)
One week block-course with exercises and presentation. Signal reconstruction from data will be trained via small programming projects of the students' own choices, followed by presentations of the achievements and experiences.
Required are a basic knowledge of Python and a laptop with installations of Python3 as well as the used Python packages "numerical python" (NumPy), "scientific python" (SciPy), and "numerical information field theory" (NIFTy) in their latest announced versions. The number of participants is limited.
The Key Qualification certificate is obtained by a presentation of the student's achievement at the end of the
Date: One week in September 2023, week is to be decided, 10:00-16:00
Location: MPI for Astrophysics, Garching
Seminar on Artificial Intelligence, Bayes, & Cognition (October 2022)
In the seminar, concepts of artificial intelligence and cognition will be discussed from a Bayesian probabilistic perspective, as for example taught in the lecture on Information Theory.
Possible topics for talks are the theory of neural networks, generative networks (following adversarial, auto-encoder, or information field theory designs), signal perception systems (receptor/measurement principles, information processing, signal extraction & reconstruction), knowledge representation (coding theory, neural networks, data compression), artificial & biological cognition (approaches, models, designs), interacting intelligent systems (game theory, computational economics, sociology, & psychology), quantum intelligence (quantum computing, quantum machine learning), and more (participants’ ideas).
The connecting element of these topics, Bayesian reasoning and information theory, should made be visible in the presentations, whenever possible. Highlighting the physics perspective (application in physics, related physical concepts, physical implementations) is encouraged, wherever appropriate.
Date: 12.10.2021 - 14.10.2021
Location: MPI for Astrophysics
Recommended prerequisite: Information (field) theory
Registration: Please register in the LSF system of the LMU between July 25th and August 14th. The number of participants is limited.