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docs/source/references.rst

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 List of references for the implemented learning algorithms, AutoML tools and baseline mutual information estimators
 
 
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 📊 Learning Algorithms
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 - `Multi-Layer Perceptron (MLP) <https://www.researchgate.net/publication/35657389_Beyond_regression_new_tools_for_prediction_and_analysis_in_the_behavioral_sciences>`_: Werbos (1974)
 - `Consistency MLP <https://dl.acm.org/doi/10.1016/S0893-6080(09)80011-7>`_: Mielniczuk et al. (1993)
 - `Random Forest (RF) <https://doi.org/10.1023/A:1010933404324>`_: Breiman (2001)
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 - `Classifier Calibration <https://dl.acm.org/doi/10.1007/s10994-023-06336-7>`_: Filho et al. (2023)
 
 
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 🤖 AutoML Tools
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 - `TabPFN <https://arxiv.org/abs/2207.01848>`_: Hollmann et al. (2023)
 - `AutoGluon <https://arxiv.org/abs/2003.06505>`_: Erickson et al. (2022)
 
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 🚀 Baseline MI Estimators
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 - `Mutual Information Neural Estimation (MINE) <https://proceedings.mlr.press/v80/belghazi18a/belghazi18a.pdf>`_: Belghazi et al. (2018)
 - `PC-softmax <https://arxiv.org/abs/1911.10688>`_: Qin et al. (2020)