2021 Lecture on Information Theory & Information Field TheoryScript Recordings Handouts Exercises Examinations
Imaging in astronomy, geology and medicine require intelligent methods to obtain high fidelity images from noisy, incomplete data. The theoretical and mathematical framework in which imaging and data analysis methods are derived should be information theory to which these lectures will introduce first (first 1/3 semester 12.04.2021-11.05.2021, 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 from data (remaining 2/3 semester, 17.05.2021-13.07.2021 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
Due to the current pandemic situation the lecture will be given as a videoconference for which a registration is necessary. The course consists of videos and their discussion in interactive life sessions.
There will be two lectures/discussion sessions per week
Information theory, begin: 12.04.2021, end: 11.05.2021
Information field theory, begin: 17.05.2021, end: 13.07.2021
- Monday, 14:00- 16:00, Internet (not Theresienstr. 37, A348)
- Tuesday, 14:00- 16:00, Internet (not Theresienstr. 37, A348)
Information theory: May 29th 2021, 10:00-12:00, (via Zoom)
Information field theory: (date to be confirmed), (probably Internet)
2021 Tutorials for Information Theory & Information Field Theory
There are three tutorials per week: Begin: 21.04.2021, End: 15.07.2021
- group A, Wednesday 16:00 - 18:00, Internet (not Theresienstr. 37, room A 248),
- group B, Thursday, 10:00 - 12:00, Internet (not Theresienstr. 37, room A 249),
- group C, Thursday, 16:00 - 18:00, Internet (not Theresienstr. 37, room A 449)
If you like to take advantage of the bonus system you must register yourself via the button found above under the lecture description.
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. 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 may present. Students need to sign up for at least 60% of all possible achievable points during each part, IT and IFT, in order to get the full bonus for the respective exam. Besides this the tutors randomly choose students to present their solutions of the work sheet on the black board. In case the student is not able to properly solve the task, instead of getting the points for this exercise he/she will receive up to twice the negative number of points he could have gained by the correct solution. It will be ensured that top marks are well reachable without the bonus. Students can ask for presenting and get double points if they are exceptionally clear and instructive in their presentation. Deadline for handing in solutions/presentations should be Monday 12:00 (exceptions possible)
Signal reconstruction with Python, EDV-Zusatzausbildung (SQ1+SQ2, September 2021)
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: some week in September 2021 (to be decided), 10:00-16:00
Location: virtual meeting
Registration: Please register in the LSF system of the LMU (link will open end July/early August)
Seminar on Artificial Intelligence, Bayes, & Cognition (October 2021)
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.
Location: MPI for Astrophysics or virtual meeting
Recommended prerequisite: Information (field) theory
Registration: Please register in the LSF system of the LMU (link will open in July)