📚 Litereture Research

List of references for the implemented learning algorithms, AutoML tools and baseline mutual information estimators

📊 Learning Algorithms

• Multi-Layer Perceptron (MLP): Werbos (1974)

• Consistency MLP: Mielniczuk et al. (1993)

• Random Forest (RF): Breiman (2001)

• Consistency RF: Biau et al. (2023)

• Extra Trees (ET): Geurts et al. (2006)

• XGBoost (XGB): Chen and Guestrin (2016)

• CatBoost (CB): Dorogush et al. (2018)

• Classifier Calibration: Filho et al. (2023)

🤖 AutoML Tools

• TabPFN: Hollmann et al. (2023)

• AutoGluon: Erickson et al. (2022)

🚀 Baseline MI Estimators

• Gaussain Mixture Model (GMM): Polo et al. (2022)

• Mutual Information Neural Estimation (MINE): Belghazi et al. (2018)

• PC-softmax: Qin et al. (2020)