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A curated list of awesome responsible machine learning resources.
Decision tree interpreter for randomForest/ranger as described in
computation of convolutional kernels (CKN and NTK) in C++
Implementation of Graph Neural Tangent Kernel (NeurIPS 2019)
Testing Nerual Tangent Kernel (NTK) on small UCI datasets
Code for NeurIPS 2019 paper: "Tensor Programs I: Wide Feedforward or Recurrent Neural Networks of Any Architecture are Gaussian Processes"
A model-agnostic visual debugging tool for machine learning
Fast and Easy Infinite Neural Networks in Python
An implementation of the minimum description length principal expert binning algorithm by Usama Fayyad
iterative Random Forests (iRF): iteratively grows weighted random forests, finds interaction among features
DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphic…
Attributing predictions made by the Inception network using the Integrated Gradients method
R package for Dynamic Factor Models with mixed frequencies and unbalanced panel 📉
Python implementation of the conformal prediction framework.
🔦 Improved incremental searching for Vim
Tutorials and implementations for "Self-normalizing networks"
A method for training neural networks that are provably robust to adversarial attacks.