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kochbj/Deep-Learning-for-Causal-Inference

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Extensive tutorials for learning how to build deep learning models for causal inference (HTE) using selection on observables in Tensorflow 2.

active 2023-08-15 → 2026-01-29 (UTC)

Complete coverage27,431 / 27,431 hourly files (100%) · 2 absent upstream2023-08-15 → 2026-09-30 (UTC)
Events
160
Pushes
14
Pull requests
0
Issues
3
Stars
122
Forks
17

Activity over time

Daily event counts in the loaded window

Line chart, 899 days from 2023-08-15 to 2026-01-29. Pushes: 14 total, peak 5 in a day. Pull requests: 0 total, peak 0 in a day. Issues: 3 total, peak 1 in a day. Comments: 4 total, peak 1 in a day. Stars: 122 total, peak 3 in a day.

  • Pushes
  • Pull requests
  • Issues
  • Comments
  • Stars

Stars, PRs, issues and forks are under-captured in the later part of this window. GH Archive progressively stopped capturing non-push events during 2026 — −95% or worse by the end of the window. Every series here except Pushes fades for that reason, so a decline above reflects the archive, not this repository. Pushes stay reliable throughout, so read them, and the contributor counts derived from them, as the real signal. Data health has the measurements.

Top contributors

Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity

ContributorContributionsPushesPRsComments
kochbj191403
xiaogangzhu2001

Recent activity

Latest issues, pull requests and releases

Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 122 stars here means stars gained during the window, not the repo's star count.