A new artificial intelligence project at ELTE
Neural network – based approximation of Dirichlet-to-Neumann maps are shown, as part of our major project in machine learning.
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Lightweight diacritic restoration for V4 languages
Diacritics restoration became a ubiquitous task in the Latin-alphabet-based English-dominated Internet language environment. We showcase a small footprint 1D convolution-based solution, running in a web browser, which surpassed the performance of similarly sized models. Many languages have alphabets where some characters are derived from other characters using diacritical marks. The […]
Read moreEstimation and simulation of fractional Ornstein-Uhlenbeck processes, using deep neural networks
There is now a great deal of interest in parameter estimation of Ornstein-Uhlenbeck processes in finance because of its modelling capability (see e.g. [1]). That is why we investigated prediction of the unknown parameters with neural networks in the hope that we will obtain more accurate estimators than the ones […]
Read moreMathematics Expert in Data Analytics and Machine Learning
A new program has started for graduates at Eötvös Loránd University: This program is for those, who want to be among the winners of the socio-economic transformations generated by artificial intelligence. It is well-known than those can make the most of the possibilities offered by artificial intelligence who well understand […]
Read moreNeural networks for boundary value problems
We report here a promising approach to use neural networks for the efficient numerical solution of boundary value problems. According to the theory of boundary integral equations and the so-called method of fundamental solutions, the principal concept is to approximate the solution by a linear combination of fundamental solutions.Neural networks […]
Read moreIn new ways in the field of medical image analysis supported by artificial intelligence
For more than a decade data mining, including machine learning has been an active topic of research and teaching at the Mathematical Institute at the Eötvös Loránd University with the objective of keeping up a good balance of mathematical and engineering approach. In recent years it was a good base […]
Read moreCOVID-19 task force of mathematical modelling and epidemiological analysis in Hungary
Research on mathematical modelling of infectious diseases has been carried out at the Bolyai Institute of the University of Szeged for already 12 years. Earlier topics studied by the research group include strategies for influenza vaccination, the impact of mandatory varicella vaccination, the risk of measles outbreaks during the 2012 […]
Read moreMarkovchart: an R package for cost-optimal patient monitoring and treatment using control charts
This post is a follow-up on our previous one from 2019: In that one we discussed Markov chain-based cost-optimal control charts briefly and gave an example for their use on the data of diabetic patients. The goal of control charts (and generally of statistical process control) is to improve a […]
Read moreA new ECMI teaching node: Eötvös Loránd University, Budapest
After two years of preparation, our new MSc program in Applied Mathematics starts this September, with approx. 10 students, mainly from the Hungarian program called Stipendium Hungaricum. The 120-credit, 2-year program is ready for launch, we look forward to it – as it is an important step towards our […]
Read moreMarkov chain-based cost-optimal control charts
Control charts can be found in many areas in industry and engineering and even in more remote disciplines. When I started working with control charts, I already had a background in biostatistics, thus I immediately started thinking about healthcare applications. The most basic role of a control chart is to […]
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