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Slides, paper notes, class notes, blog posts, and research on ML 📉, statistics 📊, and AI 🤖.

Source for csinva.io

SlidesResearch overviewsCheat sheetsNotes
PostsResearch linksPersonal info
@csinva_

Slides

The pres folder contains source for presentations, including ML slides from teaching machine learning at berkeley The source is in markdown (built with reveal-md) and is easily editable / exportable

Research and class notes

The research_ovws folder contains overviews and summaries of recent papers in different research areas

interp

The _notes folder contains markdown notes and cheat-sheets for many different courses and areas between computer science, statistics, and neuroscience

notes

Code

Links/explanations of research code, such as these repos:

Interpretable machine learning Interpretable deep learning Deep learning fun
imodels: transparent model library (e.g. FIGS + HS), DAC: disentangled attribution curves ACD: hierarchical interpretations, TRIM: interpreting transformations, CDEP: penalizing explanations, AWD: adaptive wavelet distillation GAN/VAE: demo models, paper-title generator with gpt2

Posts

Posts on various aspects of machine learning / statistics / neuroscience advancements

Interpretability Connectomics Disentanglement

Reference