Csinva.github.io

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Hi 👋 I'm Chandan, a Senior Researcher at Microsoft Research working on interpretable machine learning. I've been compulsively taking / improving my notes since my PhD at UC Berkeley and share them on this website. Hope they're helpful :)

<p align="center"> <a href="pres">Slides</a> • <a href="_notes/research_ovws">Research overviews</a> • <a href="_notes/cheat_sheets">Cheat sheets</a> • <a href="_notes">Notes</a> <br> <a href="_blog">Blog posts</a> • <a href="https://scholar.google.com/citations?hl=en&user=XpttKK8AAAAJ&view_op=list_works&sortby=pubdate">Personal info</a> <br> <a href="https://twitter.com/csinva">@csinva</a> </p>

Slides

<details> <summary>The <a href="pres">pres</a> folder contains source for presentations, including <a href="https://csinva.github.io/pres/189/#/">ML slides</a> from teaching machine learning at berkeley</summary> The source is in markdown (<a href="https://csinva.io/blog/misc/reveal_md_enhanced/readme">built with reveal-md</a>) and is easily editable / exportable <ul> <li><a href="https://csinva.io/pres/189/#/">ML slides (berkeley cs 189)</a></li> <li><a href="https://csinva.io/pres/188/#/">AI slides (berkeley cs 188)</a></li> <li><a href="https://docs.google.com/presentation/d/1RIdbV279r20marRrN0b1bu2z9STkrivsMDa_Dauk8kE/present?slide=id.p">Interpretability workshop</a></li> <li><a href="https://docs.google.com/presentation/d/1cdzZsyRYRs9GiR9s2-V7OO8oIcaabT5TVJFGR9qk_HY/present?slide=id.p">Disentangled interpretations</a></li> </ul> </details>

Research and class notes

<details> <summary>The <a href="_notes/research_ovws">research_ovws</a> folder contains overviews and summaries of recent papers in different research areas</summary> <ul> <li><a href="https://github.com/csinva/csinva.github.io/blob/master/_notes/research_ovws/ovw_interp.md">Interpretability</a></li> <li><a href="https://csinva.io/notes/research_ovws/ovw_causal_inference.html">Causal inference</a></li> <li><a href="https://csinva.io/notes/research_ovws/ovw_transfer_learning.html">Transfer learning</a></li> <li><a href="https://csinva.io/notes/research_ovws/ovw_uncertainty.html">Uncertainty</a></li> <li><a href="https://github.com/csinva/csinva.github.io/blob/master/_notes/research_ovws/ovw_dl_theory.md">DL theory</a></li> <li><a href="https://github.com/csinva/csinva.github.io/blob/master/_notes/research_ovws/ovw_complexity.md">Complexity</a></li> <li><a href="https://github.com/csinva/csinva.github.io/blob/master/_notes/research_ovws/ovw_scat.md">Scattering transform</a></li> <li><a href="https://github.com/csinva/csinva.github.io/blob/master/_notes/research_ovws/ovw_dl_for_neuro.md">DL in neuroscience</a></li> </ul> </details>

<details> <summary>The <a href="_notes">_notes</a> folder contains markdown notes and <a href="_notes/cheat_sheets">cheat-sheets</a> for many different courses and areas between computer science, statistics, and neuroscience</summary> <ul> <li><a href="https://csinva.io/notes/cheat_sheets/interp.svg">Interpretability cheat sheet</a></li> <li><a href="https://csinva.io/notes/neuro/comp_neuro.html">Computational neuroscience</a></li> <li><a href="https://csinva.io/notes/stat/causal_inference.html">Causal inference notes</a></li> <li><a href="https://csinva.io/notes/ml/classification.html">Classification</a></li> <li><a href="https://csinva.io/notes/math/linear_algebra.html">Linear algebra</a></li> <li><a href="https://csinva.io/notes/stat/info_theory.html">Info theory</a></li> <li><a href="https://csinva.io/notes/ml/comp_vision.html">Computer vision</a></li> <li><a href="https://csinva.io/#:~:text=A%20rough%20set%20of%20notes%20which%20may%20serve%20as%20useful%20reference%20for%20people%20in%20machine%20learning%20/%20neuroscience.">Way more notes here</a></li> </ul> </details>

Posts

Posts on various aspects of machine learning / statistics / neuroscience advancements (some selected posts below)

• paper writing tips(2023)
• forecasting paper titles (2022)
• imodels (2022, bairblog)

Reference

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