Stars
Understanding Deep Learning - Simon J.D. Prince
"Deep Generative Modeling": Introductory Examples
A review of papers proposing novel GNN methods with application to brain connectivity published in 2017-2020.
A Python package for causal inference in quasi-experimental settings
Anomaly detection related books, papers, videos, and toolboxes
Graph Neural Network Library for PyTorch
Curated list of awesome GAN applications and demo
A collection of learning resources for curious software engineers
Tigramite is a python package for causal inference with a focus on time series data. The Tigramite documentation is at
Brain graph super-resolution using graph neural networks.
Graph SuperResolution Network using geometric deep learning.
A curated list of causal inference libraries, resources, and applications.
Choice modeling with PyTorch: logit model and nested logit model
Repository for the free online book Machine Learning from Scratch (link below!)
This curated list contains python packages for time series analysis
Free online textbook of Jupyter notebooks for fast.ai Computational Linear Algebra course
A use-case focused tutorial for time series forecasting with python
Data, Benchmarks, and methods submitted to the M5 forecasting competition
This repository consolidates my teaching material for "Causal Machine Learning".
Must-read papers and resources related to causal inference and machine (deep) learning
Generate Diverse Counterfactual Explanations for any machine learning model.
A collection of reference Jupyter notebooks and demo AI/ML applications for enterprise use cases: marketing, pricing, supply chain, smart manufacturing, and more.
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…
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…
A full example for causal inference on real-world retail data, for elasticity estimation
Repository of notes, code and notebooks in Python for the book Pattern Recognition and Machine Learning by Christopher Bishop
The open source repository for the Causal Modeling in Machine Learning Workshop at Altdeep.ai @ www.altdeep.ai/courses/causalML