alibi-detect VS zotero

Numerous tools exist for detecting anomalies in time series data, but Alibi Detect stood out to me, particularly for its capabilities and its compatibility with both TensorFlow and PyTorch backends.

That is, to see whether a test image belongs in the distribution of the training images and to provide a routine for special cases. After a bit of reading Ive found that this is related to the field of drift detection in which I tried out alibi-detect . Whereby the training images are trained by an autoencoder and any subsequent drift will be flagged by the AE.

Wasserstein distance is not very suitable for drift detection on most problems given that the sample complexity (and estimation error) scales with O(n^(-1/d)) with n the number of instances (100k-10m in your case) and d the feature dimension (192 in your case). More interesting will be to use for instance a detector based on the maximum mean discrepancy (MMD) with estimation error of O(n^(-1/2)). Notice the absence of the feature dimension here. You can find scalable implementations in Alibi Detect (disclosure: I am a contributor): MMD docs, image example. We just added the KeOps backend for the MMD detector to scale and speed up the drift detector further, so if you install from master, you can leverage this backend and easily scale the detector to 1mn instances on e.g. 1 RTX2080Ti GPU. Check this example for more info.

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* https://github.com/SeldonIO/alibi

* https://github.com/SeldonIO/alibi-detect

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I work in this area and also contribute to outlier/drift detection library https://github.com/SeldonIO/alibi-detect. To tackle this type of problem, I would strongly encourage following a more principled, fundamentally (statistically) sound approach. So for instance measuring metrics such as the KL-divergence (or many other f-divergences) will not be that informative since it has a lot of undesirable properties for the problem at hand (in order to be informative requires already overlapping distributions P and Q, it is asymmetric, not a real distance metric, will not scale well with data dimensionality etc). So you should probably look at Integral Probability Metrics (IPMs) such as the Maximum Mean Discrepancy (MMD) instead which have much nicer behaviour to monitor drift. I highly recommend the Interpretable Comparison of Distributions and Models NeurIPS workshop talks for more in-depth background.

All of the above functionality and more can be easily used under a simple API in https://github.com/SeldonIO/alibi-detect.

Maybe try Zotero[1]. There are many addons which can do what you need.

[1]https://www.zotero.org/

And next time, you use a real literature management program like zotero (some university libraries offer classes, there is a r/zotero, etc) or jabref to create a proper bibtex file with the references. It is not that difficult, and keeps you sane (esp. if a paper has to be formatted for a different publisher). See e.g. learnlatex.

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Zotero is an open-source project that develops software to help people collect, organize, annotate, cite, and share their research. Our software is recommended by most universities and used by millions of students, scholars, scientists, and researchers worldwide.

We're looking for a JavaScript developer to work on Zotero "translators" — the pieces of code that let people click a button in their browser toolbar on any webpage and save high-quality metadata and files to their Zotero libraries. If you like web scraping, APIs, data formats, and exploring sites in the browser devtools, this would be up your alley. As a core Zotero developer, you'll also have the ability to work across Zotero's vast ecosystem and help shape the future of the project.

This is an open-ended contract role that can scale up and down in hours based on availability and workload.

https://www.zotero.org/jobs

Zotero is your answer, it even auto generates your citations.

https://www.zotero.org/

Apparently there are plugins for Logseq and Obsidian as well.

Zotero - Price: Free Free and open-source reference manager that helps you collect, organize, and cite your research sources.

I use the free and open source Zotero which I think you'd find very calibre-like and manage notes and concept linking with org-roam in emacs.

If you can't hold the urge to know, you can check on the Zotero web library if all of your things are still there

Resources: ZOTERO. Zotero is a free (you can pay to get more storage), open-source citation manager with optional browser plugins. IT WILL FORMAT CITATIONS FOR YOU. (sometimes you have to edit them, but most of the time it can pull metadata and format things correctly on its own). You can sort your references into folders or with tags, read and annotate PDF copies on your computer or in a mobile app, and make notes - which I used to keep track of specific quotations I wanted to use.

You can also use online resources like The Encyclopedia of Archaeological Sciences, that I think is mostly free or the Handbook of Archaeological Sciences which I think is also mostly free. If you can't get a hold of those things you can also email the authors/editors and they might send you a free copy or look them up on Academia.edu and see if they have a free version. Also, if you don't already, use Google Scholar, it's the best resource for finding free articles and topics to read. It's also never too early to start using something like Zotaro, Mendeley, or Endnote to keep track of your readings and help you with citations/references in papers. You can literally download the citation, import it into one of those systems and it automatically formats your referencing.