Ronan Perry

An interesting repository and related paper here on performing two-sample tests using auto-ML (or any particular model you want) to fit classes and perform powerful two sample tests. https://github.com/jmkuebler/auto-tst

Kernel Conditional Independence Tests

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Testing for conditional independence, X \indep Y | Z, is a common problem within causal discovery and feature selection. The following two kernel-based methods are able to perform this test...

A new correlation coefficient

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I've seen some recent discussions surrounding the paper [A new coefficient of correlation](https://arxiv.org/pdf/1909.10140.pdf) which basically introduces a nonparametric alternative to the spearman/kendal correlation coefficients which is just as simple but...

Popular 2-sample tests often measure the difference in means or the conditional difference in means. Tests such as MMD test for differences in distribution, generalizing past only the first moment...

Modify Projection Distribution for Time Series Data

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1. Remove continuity requirement in one dimension to allow for data such as multivariate time series 2. Obtain results on EEG kaggle dataset (https://www.kaggle.com/c/grasp-and-lift-eeg-detection/data) - Mean squared error plot for...

When oob=True, the classification accuracy doesn't match oob=False and also shows variability even with a set seed. ```python from rerf.rerfClassifier import rerfClassifier # Import scikit-learn dataset library from sklearn import...

Investigate combined honest trees + isotonic calibration

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## Background Honest decision trees build upon conventional decision trees by splitting the samples into two sets: one for learning the decision tree structure and the other for learning the...

Contrastive learning transformer for PL Network

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### Background Currently, the progressive learning network transformer is learned as a byproduct of optimizing the softmax objective loss for classification accuracy. Contrastive loss ([reference 1](https://arxiv.org/abs/2004.11362), [reference 2](https://arxiv.org/pdf/2002.05709.pdf)) explicitly learns...

#### Reference issue None #### Type of change Feature request #### What does this implement/fix? Adds additional parameters to Uncertainty Forest to better match the generalized random forest implementations in...