Page Not Found
Page not found. Your pixels are in another canvas.
Sitemap
A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
Vyacheslav Kungurtsev
Optimization, control, scientific AI, and computation from HPC to embedded autonomy.
Page not in menu
This is a page not in th emain menu
Posts
Future Blog Post
Published:
This post will show up by default. To disable scheduling of future posts, edit config.yml and set future: false.
OORDSU: from offline HPC to online embedded decisions
Published:
Introducing OORDSU: a research program connecting expensive offline HPC with adaptive, real-time decision making on embedded systems under uncertainty.
What do we mean when we say one thing “causes” another?
Published:
A summary of our ordinary-language critique of causal machine learning: causal claims acquire their meaning from mechanisms and scientific domains, not from a single domain-independent mathematical formalism.
Blog Post number 4
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 3
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 2
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 1
Published:
portfolio
Lifted Relational Neural Networks
A custom framework for deep relational learning, written completely from scratch in Java (with a Python frontend)
see my NeuraLogic repository
date: 2015-2020
role: developer
End-to-end learning of optimal portfolios
Focus on principled combining of machine learning and subsequent (portfolio) optimization problems.
date: 2020-present
role: lead researcher
funding: Czech Science Foundation
Deep Relational Learning
Developing novel algorithms for transferring neural network methods into relational learning setting.
date: 2017-2019
role: lead researcher
funding: Czech Science Foundation
Machine learning for network security
Developing machine learning methods and sound algorithms to detect malicious events from NetFlow traffic.
date: 2013-2015
role: researcher
funding: Cisco R&D
Machine learning methods for bio-informatics
Developing various novel machine learning methods for data analysis in bio-informatics (and beyond).
date: 2017-present
role: coordinator (PI)
funding: Czech Technical University
publications
Lifted Relational Neural Networks: Efficient Learning of Latent Relational Structures
Published in Journal of Artificial Intelligence Research, 2015
This paper introduces our original concept of Lifted Relational Neural Networks (LRNN, from 2015)
Download here
Events from network flows
Published in US patent office, 2016
US patent - A constructive procedure for detection of malicious network events from NetFlow traffic.
Download here
Stacked Structure Learning for Lifted Relational Neural Networks
Published in International Conference on Inductive Logic Programming, 2017
A structure learning extension of the LRNN concept - we won the best paper of the conference with it.
Download here
Beyond Graph Neural Networks with Lifted Relational Neural Networks
Published in Machine Learning Journal, 2020
We show how the Lifted Relational Neural Networks concept covers the Graph Neural Networks concept (and more)
Download here
Beating the market with a bad predictive model
Published in International Journal of Forecasting, 2020
I wrote this paper to closely explain our previous concept of exploiting sports betting market with ML
Download here
Lossless compression of structured convolutional models via lifting
Published in International Conference on Learning Representations (ICLR), 2021
We introduce a lossless compression technique to significantly speed up models such as Graph Neural Networks
Download here
Deep Learning with Relational Logic Representations
Published in Czech Technical University press (theses), 2021
This is actually my dissertation thesis - it contains my work on deep relational learning.
Download here
talks
Talk 1 on Relevant Topic in Your Field
Published:
This is a description of your talk, which is a markdown files that can be all markdown-ified like any other post. Yay markdown!
Conference Proceeding talk 3 on Relevant Topic in Your Field
Published:
This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.
teaching
Functional and Logic Programming
Undergraduate course, Czech Technical University, Computer Science, 2016
duration: 2014-2017
role: tutor
Course website
Introduction to Natural Language Processing
Undergraduate course, Czech Technical University + MatFyz @ UK, Computer Science, 2016
duration: 2017-2019
role: organizer
Course website
Machine Learning and Data Analysis
Graduate course, Czech Technical University, Computer Science, 2017
duration: 2013-2018
role: tutor
Course website
Database Systems
Undergraduate course, Czech Technical University, Computer Science, 2020
duration: 2018-present
role: tutor
Course website
Symbolic Machine Learning
Graduate course, Czech Technical University, Computer Science, 2022
duration: 2022-present
role: lecturer + tutor
Course website