reading list

Papers by others that I have enjoyed and would recommend, each with a short personal note. These are not my own publications.

These are papers by others that I have enjoyed and recommend — not my own work (for that, see my publications). Each comes with a short personal note.

  1. An Algebraic Framework for Runtime Verification
    Stefan Jakšić, Ezio Bartocci, Radu Grosu, and Dejan Ničković
    IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2018
     Felix’s note

    This is the paper that got me into research. I read it before my first internship at AIT many years ago. I have a soft spot for algebra and found this a really pretty way to use it in a somewhat applied setting. So far, I haven’t really done much with ARV (except use it in our RoadLogic paper for the boolean monitors), but maybe some day I have a cool followup idea for it. I keep forgetting the technical details, I must have read it a couple times over the years.

    JOURNAL · TCAD
  2. Timed regular expressions
    Eugene Asarin, Paul Caspi, and Oded Maler
    Journal of the ACM, 2002
     Felix’s note

    This is the original paper for timed regular expressions. Essentially they are like regular expressions, but they read words with real valued delays between the letters. I think this is a quite interesting structure and it deserves a read.

    JOURNAL · JACM
  3. The role of artificial intelligence in disinformation
    Noémi Bontridder and Yves Poullet
    Data & Policy, 2021
     Felix’s note

    This is an ethics paper about some of the negative impacts of AI. I read it as part of an AI ethics course at TU Vienna and I think it is good to discuss the social impact of our work.

    JOURNAL · DAP
  4. The lottery ticket hypothesis: Finding sparse, trainable neural networks
    Jonathan Frankle and Michael Carbin
    arXiv preprint arXiv:1803.03635, 2018
     Felix’s note

    I thought this was a fun little idea: by randomly initializing networks and then killing the right edges, one can get good networks. And they are sparser! Huang et al. (2022) lift the hypothesis to graph neural networks and verify it experimentally.

    PREPRINT · arXiv
  5. Axiomatic Set Theory
    Patrick Suppes
    1972
     Felix’s note

    A classic textbook on set theory. I read the part on Alephs and Ordinals, quite fascinating.

    BOOK · Suppes