andreaskapou

lightning

Deep learning framework to train, deploy, and ship AI products Lightning fast.

Top2Vec

Top2Vec learns jointly embedded topic, document and word vectors.

scvi-tools

Deep probabilistic analysis of single-cell and spatial omics data

tomotopy

Python package of Tomoto, the Topic Modeling Tool

ArtofStatistics

Code for 'The Art of Statistics'

svae

code for Structured Variational Autoencoders

cellrank

CellRank: dynamics from multi-view single-cell data

cell2location

Comprehensive mapping of tissue cell architecture via integrated single cell and spatial transcriptomics (cell2location model)

spacexr

Spatial-eXpression-R: Cell type identification (including cell type mixtures) and cell type-specific differential expression for spatial transcriptomics

stLearn

A novel machine learning pipeline to analyse spatial transcriptomics data

LFTM

Improving topic models LDA and DMM (one-topic-per-document model for short texts) with word embeddings (TACL 2015)

pyrelational

pyrelational is a python active learning library for rapidly implementing active learning pipelines from data management, model development (and Bayesian approximation), to creating novel active learning strategies.

CellTrek

awesome-topic-models

✨ Awesome - A curated list of amazing Topic Models (implementations, libraries, and resources)

fastTopics

Fast algorithms for fitting topic models and non-negative matrix factorizations to count data.

scaden

Deep Learning based cell composition analysis with Scaden.

scimap

Spatial Single-Cell Analysis Toolkit

lda4rec

🧮 Extended Latent Dirichlet Allocation for Collaborative Filtering in Recommender Systems.

vae-playground

Implementation of Variational Autoencoders using Pytorch Lightning

spatial_lda

Probabilistic topic model for identifying cellular micro-environments.

NeuralDecomposition

PyTorch implementation of the paper "Neural Decomposition: Functional ANOVA with Variational Autoencoders"

FISHFactor

A probabilistic factor model for spatial transcriptomics data with subcellular resolution

STRIDE

STRIDE (Spatial TRanscRIptomics DEconvolution by topic modelling) is a cell-type deconvolution tool for spatial transcriptomics by using single-cell transcriptomics data.

sparse-constrained-lda

RImageJROI

R package to read ImageJ ROI files

CRFTM

Incorporating Word Embeddings into Topic Modeling of Short Texts

TBLDA

Telescoping Bimodal Latent Dirichlet Allocation

MRF-LDA

MRF-LDA model for topic modelling

ldapaper

smfishhmrf-r