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Readings for "A Unified View of Relational Deep Learning for Drug Pair Scoring." (IJCAI 2022)
The main features of astrazeneca/awesome-drug-pair-scoring are: Awesome List, Curated Knowledge Bases, Curated Resource Lists.
Projects with overlapping indexed features include: benedekrozemberczki/awesome-fraud-detection-papers — A curated list of data mining papers about fraud detection. benedekrozemberczki/awesome-monte-carlo-tree-search-papers — A curated list of Monte Carlo tree search papers with implementations. benedekrozemberczki/awesome-decision-tree-papers — A collection of research papers on decision, classification and regression trees with implementations. awesomedata/awesome-public-datasets — This project is a community-maintained, open-access directory of high-quality public datasets. It serves as a… astrazeneca/awesome-explainable-graph-reasoning — A collection of research papers and software related to explainability in graph machine learning. jospolfliet/awesome-ai-usecases — A list of awesome and proven Artificial Intelligence use cases and applications.
A collection of research papers on decision, classification and regression trees with implementations.
A collection of research papers and software related to explainability in graph machine learning.
This project is a community-maintained, open-access directory of high-quality public datasets. It serves as a centralized reference point for researchers, developers, and data scientists to locate reliable information sources across a wide spectrum of industries and scientific fields. By providing a structured index, the repository facilitates the discovery of data necessary for exploratory analysis, machine learning model training, and the development of data-intensive applications. The directory distinguishes itself through a lightweight, platform-agnostic approach to resource indexing that
A curated list of data mining papers about fraud detection.