I’ve been diving a lot deeper into some interesting neural network papers recently and I’m looking to try and implement some of the models detailed in the papers. In general, I know that many papers include the code or I can just google the code to implement the model but I want to push myself to start implementing from scratch more.

Could anyone offer some tips on how they got started or gained the skills to be able to implement a model effectively within a few hours? Any advice would be much appreciated!

    • DollyNorman@alien.topBEnglish
      1·
      1 year ago

      I think this is why implementing is such a useful learning tool. Papers I tried to implement I probably read cover-to-cover 10 or 20 times, as opposed just skimming abstract, method, results.

      When missing key info, after searching the paper a few times:

      • my first step was see if I could find anything on paperswithcode or github.
      • failing that, google searches. see if I could find anything on forums, stack exchange sites, reddit.
      • uni library or academic paper web search engines
      • see if any papers that cite the paper I’m implementing give some clue
      • last resort was to look into papers they cite.

      That was all the tricks I had, keen to know any more.

      • DryArmPits@alien.topBEnglish
        1·
        1 year ago

        You can also contact the authors to ask them. Most of us are not monsters and will happily talk about our work. :)

      • Ifkaluva@alien.topBEnglish
        1·
        1 year ago

        What do you do if you find a reference implementation? Just run it? Try to implement from scratch?

        • DollyNorman@alien.topBEnglish
          1·
          1 year ago

          I tried to copy as much as possible from the paper, then fill in the blanks with how I would have solved it. I only had a partial solution but I still learnt heaps more than just reading the paper.