R package to correct measurement biases in gene methylation analyses
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Updated
May 24, 2024 - R
R package to correct measurement biases in gene methylation analyses
Indirect inference bias correction for nonlinear panel
Novel ultrafast suite for high-throughput & high-content multiparameter screening as in drug discovery. It has unique modules for QC, bias correction, similarity measurement, clustering and visualization. It can process hundreds of samples with many markers in a few hours not days & circumvents bath effect. It couples with any plate reader.
Code accompanying the thesis project: "Understanding and Correcting Selection Bias in the Sentiments derived from Flemish Tweets".
The AssayCorrector eliminates spatial bias in HTS assays using PMP methods.
🛒 Webscraper used to detect bias in Amazon product reviews for a product. Bias is determined through an original and rigorous algorithm, with the goal of producing a new, corrected, product star review from 1 to 5 based only on reviews that are considered to be 'unbiased'.
❗ This is a modified version of the CRAN R package repository. bife — Binary Choice Models with Fixed Effects
R package providing a shiny GUI to the functions implemented in rBiasCorrection
Performmance/execution time test of the bias correction tool BiasAdjustCXX v1.8 in comparison to python-cmethods v0.6.1 and xclim v0.40.0.
Code to Bias Correct ICAR output based on Livneh data, using quantile mapping.
An efficient and effective Bayesian calibration apporach for large-scale raw numerical model outputs
Scripts that I've used during grad school for data collection, analysis, visualization, cleaning, wrangling, etc., for classes, project reports, and manuscripts.
Computation and visualization of standardized mean differences from simulated data
Reveal to Revise: An Explainable AI Life Cycle for Iterative Bias Correction of Deep Models. Paper presented at MICCAI 2023 conference.
This repository contains the firth bias reduction experiments on the few-shot distribution calibration method conducted in the ICLR 2022 spotlight paper "On the Importance of Firth Bias Reduction in Few-Shot Classification".
Experiments on biases in data & models
Research POC on the mitigation of bias in large language models (FLAN-T5 and Bloomz) through fine-tuning.
Use bootstrap resampling to estimate the sampling distribution of a statistic
Tackling Gender and Race bias in Word Embeddings
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