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Code for "Heterogeneous Graph Transformer" (WWW'20), which is based on pytorch_geometric
A collection of ORM-style clients to public patent data
A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning
A large-scale open data lake for the science of science research.
Background Music, a macOS audio utility: automatically pause your music, set individual apps' volumes and record system audio.
Beautiful Interactive tables in your Flask templates.
OpenAlex Networks is a helper library to process and obtain data from the OpenAlex dataset via API. It also provides functionality to generate citation and coauthorship networks from queries.
A (PyTorch) imbalanced dataset sampler for oversampling low frequent classes and undersampling high frequent ones.
official implementation for the paper "Simplifying Graph Convolutional Networks"
🔺 Ternary plotting library for python with matplotlib
A web-based framework to visualize dynamic networks in real-time.
A Python library that interfaces with the MediaWiki API. This is a mirror from gerrit.wikimedia.org. Do not submit any patches here. See https://www.mediawiki.org/wiki/Developer_account for contrib…
Simulated institution growth and scaling created for paper entitled, "The Emergence of Heterogeneous Scaling in Research Institutions" by Keith Burghardt, Zihao He, Allon Percus, and Kristina Lerman
Workshop on Network Science
EasyGraph is an open-source network analysis library designed to cover advanced network processing methods. It includes functionalities for detecting structural hole spanners, network embedding, an…
Utilities for formatting matplotlib figures
A collection of Jupyter notebooks, each walking you through a common example of bibliometric analysis using scholarly data from the OpenAlex API.
Extracting the multiscale backbone of complex weighted networks (Serrano et al. 2009)
Calculate the Gini coefficient of a numpy array.
Collection of public APIs for embedding scientific papers
This repository contains machine readable (xml) search queries (crafted from a controlled vocabulary), for the Scopus publication database, to find domain specific research output that are related …
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
Using stochastic block models for topic modeling