hbaniecki

adversarial-explainable-ai

💡 Adversarial attacks on explanations and how to defend them

courses-iml-xai

Courses related to interpretable machine learning & explainable AI

manipulating-shap

Manipulating SHAP via Adversarial Data Perturbations (AAAI 2022)

robust-feature-effects

Robustness of Global Feature Effect Explanations (ECML PKDD 2024)

talks

contributed talks, posters, and workshops

user-21

Demo for the useR! 2021 conference talk

shapiq

Shapley Interactions for Machine Learning

DALEX

moDel Agnostic Language for Exploration and eXplanation

modelStudio

📍 Interactive Studio for Explanatory Model Analysis

survex

Explainable Machine Learning in Survival Analysis

hbaniecki/adversarial-explainable-ai

💡 Adversarial attacks on explanations and how to defend them

hbaniecki/talks

contributed talks, posters, and workshops

hbaniecki/user-21

Demo for the useR! 2021 conference talk

hbaniecki/courses-iml-xai

Courses related to interpretable machine learning & explainable AI

hbaniecki/manipulating-shap

Manipulating SHAP via Adversarial Data Perturbations (AAAI 2022)

hbaniecki/hbaniecki

hbaniecki/OpenXAI

OpenXAI : Towards a Transparent Evaluation of Model Explanations

hbaniecki/Pre-Surv-COVID-19

hbaniecki/robust-feature-effects

Robustness of Global Feature Effect Explanations (ECML PKDD 2024)

hbaniecki/compress-then-explain

Efficient and Accurate Explanation Estimation with Distribution Compression (ICML 2024 Workshops)

hbaniecki/sage

For calculating global feature importance using Shapley values.

hbaniecki/soproject

[course project '2018] Data analysis of Stack Overflow API in Java