clairemcwhite

rayshader

R Package for 2D and 3D mapping and data visualization

transformers-interpret

Model explainability that works seamlessly with 🤗 transformers. Explain your transformers model in just 2 lines of code.

word2vec-graph

Exploring word2vec embeddings as a graph of nearest neighbors

LGL

Large Graph Layout

natural-regex

Create regex from natural language

knowledge-neurons

A library for finding knowledge neurons in pretrained transformer models.

spark-social-science

Automated Spark Cluster Builds with RStudio or PySpark for Policy Research

AlphaFold2-IDR-complex-prediction

alphafold_singularity

Singularity recipe for AlphaFold

mysql-dump-to-csv

Script to parse a mysql dump and generate CSVs for all of the tables in the dump

gnomad_python_api

🧬 gnomAD Python API is used to obtain data from gnomAD (genome aggregation database).

bert-fold

who

Data from the World Health Organisation

influenza_HA_evolution

MCL-WiC

Research on Multilingual and Cross-lingual Word-in-Context Disambiguation

SRAGPU-nf

A Nextflow workflow that utilizes GPU enabled Singularity containers to process scRNA-seq data

pepliner

Pepliner: tools to visualize protein/peptide elutions

dca-weighting

new_school_nf

AdaptGauss

Multimodal distributions can be modelled as a mixture of components. The model is derived using the Pareto Density Estimation (PDE) for an estimation of the pdf. PDE has been designed in particular to identify groups/classes in a dataset. Precise limits for the classes can be calculated using the theorem of Bayes.