Large collection of machine learning paper notes (+1 paper a day)

This page summarizes the projects mentioned and recommended in the original post on news.ycombinator.com

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  • SurveyJS - Open-Source JSON Form Builder to Create Dynamic Forms Right in Your App
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  • react-notion

    A fast React renderer for Notion pages

  • It would make sense to not have server-side rendering if you're building both browser and desktop apps, since that would mean avoiding a separate framework only for the browser.

    Another clue is that people who try to use Notion as a CMS for their blogs had to build out a React library to emulate the feel of Notion itself: https://github.com/splitbee/react-notion https://github.com/NotionX/react-notion-x.

  • react-notion-x

    Fast and accurate React renderer for Notion. TS batteries included. ⚡️

  • It would make sense to not have server-side rendering if you're building both browser and desktop apps, since that would mean avoiding a separate framework only for the browser.

    Another clue is that people who try to use Notion as a CMS for their blogs had to build out a React library to emulate the feel of Notion itself: https://github.com/splitbee/react-notion https://github.com/NotionX/react-notion-x.

  • SurveyJS

    Open-Source JSON Form Builder to Create Dynamic Forms Right in Your App. With SurveyJS form UI libraries, you can build and style forms in a fully-integrated drag & drop form builder, render them in your JS app, and store form submission data in any backend, inc. PHP, ASP.NET Core, and Node.js.

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  • ed4

    Computational Cognitive Neuroscience, Fourth Edition

  • Hm that's difficult. Automatic speech recognition (ASR) is probably by now my comfort zone.

    So already most pure DL papers are out of this zone, but I anyway many of them, when I find them interesting. Although I tend to find it a bit boring when you just adopt next-great-model (e.g. Transformer, or whatever comes next) to ASR, but most improvements in ASR are just due to that. You know, I'm also interested in all these things like neural turing machine, although I never really got a chance to apply them to anything I work on. But maybe on language modeling. Language modeling is anyway great, as it is simple conceptually, you can directly apply most models to it, and (big) improvements would usually directly carry over to WER.

    Attention-based encoder-decoder models started in machine translation (MT). And this was anyway sth part of our team did (although our team was mostly divided into the ASR and MT team). And since that came up, it was clear that this should in principle also work on ASR. It was very helpful to get a good baseline from the MT team to work on, and then to reimplement it in my own framework (by importing model parameters in the end, and dumping hidden state during beam search, to make sure it is 100% correct). And then take most recent techniques from MT, and adapt them to ASR. Others did that as well, but I had the chance to use some more recent methods, and also things like subword units (BPE) which was not standard in ASR by then. Just adopting this got me some very nice results (and a nice paper in the end). So I try to follow up on MT sometime to see what I can use for ASR.

    Then out of own interest, I'm also interested in RL. And there are some ideas you can also take over to ASR (and have been already). Although this is somewhat limited. Min expected WER training (like policy gradient) has independently already developed in the ASR field, but it's interesting to see relations, and adopt RL ideas. E.g. actor critic might be useful (has already be done, but only limited so far).

    Another field, even further away, is computational neuroscience. I have taken some Coursera course on this, and regularly read papers, although I don't really understand them in depth. But this is sth which really interests me. I'm closely following all the work by Randall O'Reilly (https://psychology.ucdavis.edu/people/oreilly). E.g. see his most recent lecture (https://compcogneuro.org/).

    This already keeps me quite busy. Although I think all of these areas can really help me advance things (well, maybe ASR, although in principle I would also like to work on more generic A(G)I stuff).

    If I would have infinite time, I would probably also study some more math, physics and biology...

  • kurin-paper-scraper

    for Vitaly Kurin's paper notes

  • Sure, I built one. I think it will work if you keep your paper collection page in the same format.

    https://github.com/arxivwiki/kurin-paper-scraper

  • arxivwiki

    crowdsourced summaries of research papers

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

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NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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