There are 1 repository under ate topic.
TreeATE是Tree Automatic Test Equipment的缩写,专注服务于工厂成品或半成品测试自动化的一种开源软件工具平台。
STDF to Wafer Bin Map utility written in Python
Adaptive debiased machine learning of treatment effects with the highly adaptive lasso
This project has scripts which can be used to compress test vectors or patterns generated to use on SoC testers like Advantest, Ultraflex. The concept is universal and can be extended to any SoC tester.
Code for causal isotonic calibration for heterogeneous treatment effects (appeared in ICML, 2023)
Extract location of pads from a kicad layout. Useful for setting testpint locations.
A domain-aware automatic term extraction tool.
Non-parametric variable selection and inference via the outcome-adaptive Random Forest (OARF). Uses the IPTW estimator to estimate the ATE while the propensity score is estimated via OARF. This leads to smaller variance and bias. Only variables that are confounders or predictive of the outcome are selected for the propensity score.
A project in the course of Causal Inference
ATE model trained on ACTER dataset (https://github.com/AylaRT/ACTER)
API to calculate odometry evaluation metrics.
Automated Test Equipment lab source code for the Master of Electronics and ICT course of Hardware Design at KU Leuven 2020-2021
Integrative analyses of the average treatment effect combining big main data and smaller validation data
Simulation of Benkeser D, Cai W, van der Laan MJ (2019+). A nonparametric super-efficient estimator of the average treatment effect.
Simple method for filling in a spreadsheet with defined equations. Useful for electronics testing.