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Stars
Code for the paper: Amortized Causal Discovery: Learning to Infer Causal Graphs from Time-Series Data
A playbook for systematically maximizing the performance of deep learning models.
A professionally curated list of awesome resources (paper, code, data, etc.) on transformers in time series.
Attention is all you need implementation
Extensive tutorials for learning how to build deep learning models for causal inference (HTE) using selection on observables in Tensorflow 2 and Pytorch.
Graph Neural Network Library for PyTorch
Platform for designing and evaluating Graph Neural Networks (GNN)