Course home

by @stats385 · last added 2026-09-24 · 10 items [home]

Hub for Stanford STATS 385 — Analyses of Deep Learning. Official site, instructors, and prior offering.

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Wed 3:00–4:20 PM meeting location for the 2019 offering — included for syllabus-style completeness.

campus-map.stanford.edu · node›

Course announcements channel used during the offering.

twitter.com · node›

Course ‘stuff everyone needs to know’ — architectures, datasets, learning motifs at a glance.

stats385.github.io · node›

Slides index on the course site. Pair with the lecture-video lists for a full week’s prep.

stats385.github.io · node›

Canonical reading list page — papers organized by lecture; mirror of what we curate thematically here.

stats385.github.io · node›

Course contact. Research on high-dimensional statistics and deep learning theory.

web.stanford.edu · node›

Course organizer / lecturer. Work on Hessians, Neural Collapse, and geometric analyses of deep nets.

statistics.stanford.edu · node›

Course instructor. Statistics & data science; foundational work on sparse recovery and high-dimensional inference.

profiles.stanford.edu · node›

Previous offering — useful to show how a course site evolves across years while keeping core themes.

stats385.github.io · node›

Official Fall 2019 course hub: guest lectures, readings, slides, and resources for Analyses of Deep Learning.

stats385.github.io · node›