# yfzhang114/Generalization-Causality

关于domain generalization，domain adaptation，causality，robutness，prompt，optimization，generative model各式各样研究的阅读笔记

Repository: https://github.com/yfzhang114/Generalization-Causality
Canonical: https://ross.abutalabs.com/products/generalization-causality
License: MIT
License Family: permissive
Topics: machine-learning, deep-learning, causality, optimization, robustness, adaptation, generative-model
Last push: 2023-12-14T13:50:13+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 1897, "days_push": 993, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1241, forks 102 (observed 2026-08-28T04:04:06.286711+00:00)

## What it is
A curated collection of academic papers with the author's personal reading notes covering domain generalization, out-of-distribution robustness, causality, test-time adaptation, prompt learning, and LLM safety. It serves as an ongoing literature survey organized by topic and year, updated with recent conference papers.

## Use cases
- find papers on domain generalization
- learn about out-of-distribution robustness research
- survey causality in machine learning
- keep up with test-time adaptation papers
- find reading notes on OOD detection
- research prompt learning and data-centric learning
- study robustness and fairness literature

## When to choose
- you want a curated, annotated reading list for OOD generalization and causality research
- you are a researcher or student surveying domain adaptation and robustness literature
- you want links to papers plus the author's own notes and related code

## When to avoid
- you need runnable software or a library rather than a paper collection
- you need exhaustive coverage rather than one researcher's curated selection
- you want notes in English - many notes link to Chinese-language articles

## Facets
- artifact type: learning-resource
- maturity: active
- function: documentation, machine-learning, deep-learning
- domain: machine-learning, deep-learning, tutorials, awesome-lists
- platform: -
- tags: reading-notes, awesome-list, domain-generalization, out-of-distribution, causality, test-time-adaptation, robustness, prompt-learning, paper-curation, web-server

## Member repositories
- yfzhang114/Generalization-Causality (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:06.286711+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T05:08:31.696856+00:00, confidence not recorded.
  - readme: https://github.com/yfzhang114/Generalization-Causality (fetched 2026-08-28T04:04:06.286711+00:00, sha 2a6d4f2a886e)
- Data as of 2026-08-30T08:39:29.467469+00:00.