Neural-Symbolic Computing Raven Beutner, Bernd Finkbeiner, Christopher Hahn, Niklas Metzger, Frederik Schmitt, Julian Siber

News

15.07.2022

Course evaluation

The Qualis course evaluation is accessible via this link until July 21. We appreciate every feedback!

06.07.2022

Change of Tomorrow’s Seminar Schedule

In tomorrow’s seminar meeting, we will have three individual talks. We will start at the usual time at 10:15 am and finish late at 12:30 pm. We hope this does not cause too much of an inconvenience for you.

22.06.2022

Tomorrow’s Seminar Meeting

Thank you for participating in the poll on tomorrow’s seminar schedule. We will start at the usual time at 10:15 am. We look forward to our first individual talks!

08.06.2022

Cancelled Seminar Meeting on June 9

Unfortunately, we have to cancel tomorrow’s seminar meeting on short notice. Our next meeting will be on June 23. Please remember to state your preference on your personal status page whether we should start early at 9:30 am or finish late at 12:30 pm on June 23.

07.06.2022

Change of Seminar Schedule June 9, June 23

Following the group phase of the seminar, we are excited to get started with the talks on your individual research papers. The first talk, about a comparison of finite automata with recurrent neural networks, will be given this Thursday.

The second talk, on... Read more

Following the group phase of the seminar, we are excited to get started with the talks on your individual research papers. The first talk, about a comparison of finite automata with recurrent neural networks, will be given this Thursday.

The second talk, on data-driven approximations to NP-hard problems, needs to be postponed to June 23. As a result, we will have three talks on June 23. Do you have a preference whether we should start early at 9:30 am or finish late at 12:30 pm? We have created a poll in the CMS so that you can let us know what you prefer. We hope this change does not cause too much of an inconvenience for you.

While preparing your talk, please feel free to reach out to your advisor. We are happy to help with questions about your paper and provide feedback.

Please be sure to attend every talk, and to participate actively in the discussions. If you attend remotely, we encourage you to turn on your camera. It is much more fun to give a talk when you can see the entire audience. If you are unable to come to one of the seminar meetings, please inform your advisor in advance.

09.05.2022

LSF Registration

Please excuse the problems with LSF registration. The department confirmed that registering for the seminar should now be possible for everyone. If any problems continue to exist, please let us know. Note that you need to register until next Monday, May 16.

04.05.2022

First Group Talk on Feedforward and Recurrent Neural Networks

As a reminder, tomorrow at 10:15 am, we will have our first group talk on feedforward and recurrent neural networks. If you would like to attend in-person, please join us in room 1.06 in E1 1. If you prefer to participate remotely, use the same Zoom link as for our... Read more

As a reminder, tomorrow at 10:15 am, we will have our first group talk on feedforward and recurrent neural networks. If you would like to attend in-person, please join us in room 1.06 in E1 1. If you prefer to participate remotely, use the same Zoom link as for our kick-off meeting, which you can also find in the information tab of the CMS.

25.04.2022

Paper Assignment

We have assigned the papers and hope to have met your preferences. You can find your paper on your personal status page. We were able to assign everyone to a paper that they rated at least good and most of you to a paper that they rated very good. Your advisor will... Read more

We have assigned the papers and hope to have met your preferences. You can find your paper on your personal status page. We were able to assign everyone to a paper that they rated at least good and most of you to a paper that they rated very good. Your advisor will reach out to you shortly to introduce you to your group.

21.04.2022

Slides, Paper Preferences, and Timetable

You can now find the slides from today’s kick-off meeting and all papers in the materials section in the CMS. On your personal status page you can enter your paper preferences until Sunday, April 24, 11:59 pm. We use the tutorial assignment mechanism of the CMS to... Read more

You can now find the slides from today’s kick-off meeting and all papers in the materials section in the CMS. On your personal status page you can enter your paper preferences until Sunday, April 24, 11:59 pm. We use the tutorial assignment mechanism of the CMS to assign the papers. The number of the tutorial slot corresponds to the paper number as found in the materials section and as presented in today’s kick-off meeting.

Our next meeting will be the presentation on feedforward and recurrent neural networks on Thursday, May 5, 10:15 am. We added all meetings to the timetable in the CMS. You can import it to your personal calendar.

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Neural-Symbolic Computing

You can register for the seminar at https://seminars.cs.uni-saarland.de/seminars22 until April 12th 23:59 CET.

The way our brain forms thoughts can be classified into two categories (according to Kahneman in his book “Thinking Fast and Slow”):

System 1: fast, automatic, frequent, stereotypic, unconscious.

  • Is this a cat or a dog?
  • What does this sentence mean in English?

System 2: slow, effortful, logical, conscious.

  • 17*16 = ?
  • If a -> b does b -> a?

The traditional view is that deep learning is limited to System 1 type of reasoning. Mostly because of the perception that deep neural networks are unable to solve complex logical reasoning tasks reliably. Historically, applications of machine learning were thus often restricted to sub-problems within larger logical frameworks, such as resolving heuristics in solvers.
In this seminar, we will explore new research that shows that deep neural networks are, in fact, able to reason on “symbolic systems”, i.e., systems that are built with symbols like programming languages or formal logics.

Example Topics:

  • What are your chances against an AI in a programming competition?
  • Is it possible to teach temporal logics to neural networks?
  • Can neural networks discover unknown connections in mathematics?

 

Requirements

Participants should have strong interest in logical reasoning and/or machine learning. There is, however, no formal prerequisite.

 

Organization

The seminar can be attended both in-person (Room 1.06 in E1 1) and remotely via Zoom.

The structure of the seminar is as follows:

In the first week of the seminar, you will choose a research paper on neural-symbolic computing.

Group Phase: Depending on your choice you will be assigned to a background topic of machine learning such as graph neural networks. In a team of three students, you will then prepare an informal lecture on your topic and the following discussion; presenting the basics to your fellow students. Each topic is assigned to an advisor that will help you with your preparations. This informal lecture will not be graded, so you can see it as a rehearsal. The group phase, thus, gives you the necessary foundations for the following individual phase.

Individual Phase: You will prepare, with the help of your advisor, a research talk on the paper you have chosen presenting the findings of the paper to your fellow students. This talk is weighted most in your final grade.

Project Phase: You will be given a neural-symbolic computing task. Each team is required to solve this problem with the methods explored in this seminar, for example by applying deep neural network architectures of your area. We do not expect own implementations of the discussed methods. You can use available libraries. This project has to be passed and it will not be graded.

 

Dates

Kick-off meeting: Thursday, April 21, at 10:15 am

Weekly meetings: Thursdays at 10:15 am



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