© TUGraz/IGI

Welcome to the Institute of Theoretical Computer Science at TU Graz

The Institute of Theoretical Computer Science was founded in 1992 to investigate fundamental problems in information processing such as the design of computer algorithms, the complexity of computations and computational models, automated knowledge acquisition (machine learning), the complexity of learning algorithms, pattern recognition with artificial neural networks, computational geometry, and information processing in biological neural systems.

Its research integrates methods from mathematics, computer science and computational neuroscience.

In education this institute is responsible for courses and seminars that introduce students into the basic techniques and results of theoretical computer science. In addition it offers advanced courses, seminars and applied computer projects in computational geometry, computational complexity theory, machine learning, and neural networks.


NEWS

Article in Nature Communications 15, Article no. 2344 (2024)

March 2024: Christoph Stöckl, Yukun Yang, Wolfgang Maass
Local Prediction-learning in High-dimensional Spaces Enables Neural Networks to Plan

Link to article

Paper accepted at IEEE Transaction on Neural Networks and Learning Systems

December 2023: Thomas Limbacher, Ozan Özdenizci, Robert Legenstein
Memory-enriched Computation and Learning in Spiking Neural Networks through Hebbian Plasticity

arXiv link to accepted paper.

Paper accepted for NeurIPS 2023

October 2023: Lorenzo Loconte, Nicola Di Mauro, Robert Peharz, Antonio Vergari
How to Turn Your Knowledge Graph Embeddings into Generative Models

arXiv link to accepted paper.

Paper accepted for AAAI 2023

October 2023: Alvaro H.C. Correia, Gennaro Gala, Erik Quaeghebeur, Cassio de Campos,
Robert Peharz - Continuous Mixtures of Tractable Probabilistic Models

arXiv link to accepted paper.

EIC Pathfinder NEO project started

October 2023: EIC Pathfinder project started
NEO, Next Generation Molecular Data Storage based on DNA Origamis

link to EU project details