Discover BenevolentAI/RELVM Open Source project by @BenevolentAI

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Python
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MIT License
Created about 4 years ago
Updated about 3 years ago

BenevolentAI

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This repository contains the code accompanying the paper "Learning Informative Representations of Biomedical Relations with Latent Variable Models", Harshil Shah and Julien Fauqueur, EMNLP SustaiNLP 2020.

guacamol

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DeeplyTough

DeeplyTough: Learning Structural Comparison of Protein Binding Sites

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guacamol_baselines

Baselines models for GuacaMol benchmarks

MolBERT

CoMP

CoMP: Contrastive Mixture of Posteriors

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ukbiobank-loaders

Python

benevolentai-dat

BenevolentAI's Diversity Analysis Tool (DAT) is a software package that can be used to produce demographic analysis reports given health data sets that contain for fields of age, sex, ethnicity, race and socio-economic status. For example, you might have a data about a cohort of patients and want to know how well you cover various ethnicities, age groups, sex groups and socio-economic status levels. Assuming your data sets have some of these fields, this software will help generate various views of the data to help inform your work. The DAT tool was developed as part of BenevolentAI's Diversity in Data Initiative, which aims to help improve the ways patients are represented in precision medicine. It is meant to help inspire other developers to find ways of assessing the data diversity in their current and prospective health data sets.

Python

funkea

Perform functional enrichment analysis at scale.

Python

guacamol_results

HTML

sre-interview

Interview scenario for Level 2 SREs

Python

BenevolentAI/RELVM

BenevolentAI

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