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Honest decision forests and trees implemented efficiently and scikit-learn compliant.
A little Python script to collect LaTeX sources for upload to the arXiv.
Move fast from data science prototype to pipeline. Capture, analyze, and transform messy notebooks into data pipelines with just two lines of code.
A library of extension and helper modules for Python's data analysis and machine learning libraries.
Python Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in Bayesian Networks.
Figure sizes, font sizes, fonts, and more configurations at minimal overhead. Fix your journal papers, conference proceedings, and other scientific publications.
Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.
Pweave is a scientific report generator and a literate programming tool for Python. It can capture the results and plots from data analysis and works well with numpy, scipy and matplotlib.
Causal Discovery in Python. It also includes (conditional) independence tests and score functions.
High performance Python GLMs with all the features!
This repo contains code and data to reproduce the results and plots of the SIGIR 2021 paper "When Fair Ranking Meets Uncertain Inference" by Avijit Ghosh, Ritam Dutt and Christo Wilson
Cookiecutter template for a simple jupyter book
Calibration of Convolutional Neural Networks
A simple way to calibrate your neural network.
ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its go…
Processing and gridding spatial data, machine-learning style
Why ReLU networks yield high-confidence predictions far away from the training data and how to mitigate the problem [CVPR 2019, oral]
Siamese and triplet networks with online pair/triplet mining in PyTorch
Collection of educational resources. Primarily focused on skills that are helpful in the NeuroData lab or the Neuro Data Design course at Johns Hopkins University.
A scikit-learn compatible neural network library that wraps PyTorch
A every-so-often-updated collection of every causality + machine learning paper submitted to arXiv in the recent past.
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…
Code and methods for COVID19 lagged mobility and sociodemographic association model US county-level
A collection of research papers on decision, classification and regression trees with implementations.
Python package for multivariate hypothesis testing
Tips for releasing research code in Machine Learning (with official NeurIPS 2020 recommendations)
reinforcement learning AI for settlers of catan