Reading list Summer 2020
Jul 25, 2020
Here’s my reading list collection for Summer 2020. I decided to denote the reading lists with seasons instead of months as I am pretty busy reading very specialized publications instead of well-elaborated books.
Ghostwritten #reading Amazon.com Erkenne die Welt #reading - history philosophy 21 Lektionen für das 21. Jahrhundert This work of Harari currently really appeals to me as it directly hits my Zeitgeist and thoughts of the last year.
Deep State Machine for Generating Graphs
Jul 17, 2020
Problem: sampling complex graphs with unknown properties learned from exemplary graph sets.
Possible solution: using a state machine with transitions learned from exemplary graphs with a setup composed of node embeddings, graph embedding, categorigcal action sampling and thoroughly chosen objectives.
Note: the real underlying problems (graph embeddings or distributions of graphs) are so difficult, we are just touching the tip of the iceberg and as soon as there would be adequate approximate solutions to it, there are going to be even more fascinating applications in medicine, chemistry, biology and machine learning itself.
Reading list April 2020
Apr 17, 2020
Here’s my reading list collection for April 2020. I found lots of those resources already some while ago. Some of them, I only scanned through and read on particular sections. It gives some kind of relief writing noteworthy links and thoughts down and I will definitely look back at several of them when my understanding of the topics changed.
The Courage To Be Disliked: How to free yourself, change your life and achieve real happiness This sokrates-style dialogue introduced me to ideas of the Psychology of Adler quite in a moment of life where I also heard of it from other sources (see e.
Obtaining priors for geographically based simulation models
Apr 08, 2020
Problem: obtain real-world statistics and process them into a graph
Solution: geopandas, shapely, rasterio, nominatim, osm-router
Incorporating real-world information into models is non-trivial. It is often done in machine learning by e.g. training models on natural images. In this post, I collect some notes and information on processing geographic statistics. Those statistics are then used in a geographically based model as described in a previous post about thoughts on simulating migration flow.
Learning just in case vs. just in time
Mar 26, 2020
Recently, I stumbled across a short blog post about learning “just in case” vs “just in time” and it got me thinking about how much I learned and later didn’t need at all and how much I learned (consciously) and now use very often.
What is learning “just in case” and “just in time”? It is the idea of dividing learning phases into the ones in which you learn something new with the expectation that the acquired skills, knowledge and understanding are of later use, and the ones in which you learn something new, because you have immediate application needs for it.
Including files in Hugo with a shortcode
Mar 25, 2020
Problem: Hugo can not simply include other files from your page bundle.
Solution: $.Page.Dir, path.Join, readFile
I usually organize larger posts in folders, e.g. this post lies under /content/posts/2020-03/include-files-hugo-shortcode/ and then the main file is an index.md. Next to it, I can add resources, which I reference locally and relatively to this main content file. This ensures, that I can easily move a post as a whole (which might include other resources such as images, code, .
Adding lightbox to Hugo
Mar 24, 2020
Problem: figures in hugo should nicely align in text and open in a lightbox
Solution: hugo, lightbox, jquery
Note, that the test images used in this post are from the MNIST database and one of Lena Forsén taken from Wikipedia and is photographed by Dwight Hooker for the Playboy Magazine.
Examples Adding a single image with plain markdown and no formatting: ![Lena Forsén](lenna-test-image-100-100.png) Adding an image with HTML, embedded in markdown: <img src="mnist-3-a.
Poetry, conda and GitLab CI
Mar 20, 2020
As I have been arguing for years that the python ecosystem urgently needs to mature its project dependency management tools, I am a very big fan of python poetry. Since it got very stable to use, I started transitioning my projects to work with a pyproject.toml instead of working with conda or setup.py (the latter I perceive as pretty complicated). It is important to note, that it always depends very strongly on the particular use case to decide for which tools to go with.
Notes on Migration Flow Simulation
Feb 28, 2020
Disclaimer: The following is a summary of technical thoughts and discussions within a large bi-lateral research project called Human+. An ethical board and social & legal research accompanied our technical investigations on the topic and we have always been in active and substantial exchange with involved aid organizations such as the Bavarian Red Cross, the Johanniter Order or the Federal Agency for Technical Relief THW. You can read on german articles at the german BMBF, at the Fraunhofer IAIS or at Kiras.
The Big Picture of my current research efforts
Feb 11, 2020
As I am still in a phase of vast exploration concerning topics around my PhD interests, I sometimes pause for a moment and try to think about the big picture. The overall theme of investigating the structure of Artificial Neural Networks (ANNs) grew organically from my always limited understanding of machine learning techniques and intuition and ideas from neuroscience and psychology. As of now, I come to the conclusion that the theme in general is way beyond my technical and formal capabilities and different empirical or methodological experiments will only converge under the guise of this theme towards an enclosed thesis.