Critical difference diagram with Wilcoxon-Holm post-hoc analysis.
[ICML'24 Oral] Rethinking Post-Hoc Search-Based Neural Approaches for Solving Large-Scale Traveling Salesman Problems
GAMLj: GLM, Mixed, Generalized and Generalized mixed models for jamovi
Python package for permutation tests, for statistics and machine learning.
Implementation of "A Large-Scale Study of Probabilistic Calibration in Neural Network Regression" (ICML 2023)
A friendly, automated chi-square test function which takes care of post-hoc tests and multiple comparisons.
UnifiedDiagnostics branch of OMNIABASE: post-hoc structural measurement beyond a single representation. structural measurement engine for invariance, drift, and epistemic limits (Ω, SEI, IRI, SNRC).
Accompanying repository for the paper "Probabilistic Calibration by Design for Neural Network Regression" (AISTATS 2024).
GUI for analyzing deep learning models with uncertainty in predictions
GAMES_HOWELL: post-hoc Games-Howell test for one-way ANOVA.
Introducing a novel lightweight, post-hoc, single-pass, model-agnostic uncertainty quantification model for pretrained deep neural networks, designed for efficiency, scalability, and compatibility.
RobustCAM fuses Grad-CAM heatmaps across augmented views to reduce spatial instability, achieving 64% variance reduction on ImageNet/VGG16 and up to 186% consistency improvement on lung CT, cross-validated with LIME and SHAP across ResNet-50/101, DenseNet-161, EfficientNet-B0, and ViT-B/16.
This project applies MANOVA to heart disease data, examining the impact of chest pain type (cp), cholesterol (chol), and heart rate (thalach). It includes normality tests, outlier detection, post-hoc analysis, and cross-validation for model evaluation.
Project about experiments of the use of ILASP as a post-hoc method over black-box models, in which we also study and approach technical issues like exponential time execution.
[ICML'24 Oral] Rethinking Post-Hoc Search-Based Neural Approaches for Solving Large-Scale Traveling Salesman Problems
Simple and multiple linear regressions, Tukey's honest significant difference analyses, and visualizations in R.
A study on post-hoc explainability in LLMs using counterfactual explanations, analyzing how model scale and prompting strategies affect explanation quality.
An R project that investigates and visualizes the effect of sex and education on an individual's income level through the use of a full-factorial two-way ANOVA test and relevant post hoc significance tests conducted over a 2014 Pew Research Center dataset consisting of higher education attainment, gender, and income data.
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