wallet-maker
Follow
Stars
Cellxgene Gateway allows you to use the Cellxgene Server provided by the Chan Zuckerberg Institute (https://github.com/chanzuckerberg/cellxgene) with multiple datasets.
Multimodal weakly supervised learning to identify disease-specific changes in single-cell atlases
Composite classifiers for modular hierarchical single cell classification
A single-cell demultiplexing pipeline, the sharp (♯)
SCING: Single-Cell pIpeliNe Garden (pronounced as "sing" /siŋ/)
Single-Cell Analysis of Inter-Individual Variability by Interpretable Tensor Decomposition
Backend library for conversational AI in biomedicine
A python library for hierarchical classification compatible with scikit-learn
Causal Variational AutoEncoders
Causal Effect Inference with Deep Latent-Variable Models
Adapted Triplet loss based metric learning to learn a metric for multilabel points, such that samples with maximum overlap in label sets are close.
Conditional Constrained Graph Variational Autoencoders (CCGVAE) for Molecule Design
An unsupervised scRNA-seq analysis workflow with graph attention networks
Implementation of Graph Auto-Encoders in TensorFlow
StellarGraph - Machine Learning on Graphs
Graph Transformer Architecture. Source code for "A Generalization of Transformer Networks to Graphs", DLG-AAAI'21.
A unifying representation of single cell expression profiles that quantifies similarity between expression states and generalizes to represent new studies without additional training.
Code and example data for running Consensus Non-negative Matrix Factorization on single-cell RNA-Seq data
A GUI to sit over top SPECTRA, a factor analysis tool built by MSKCC.
Making Protein folding accessible to all!
SEACells algorithm for Inference of transcriptional and epigenomic cellular states from single-cell genomics data
Single cell omics biology annotations
Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service.
A multi-view latent variable model with domain-informed structured sparsity for integrating noisy feature sets.
Python/C implementation of Hartigan & Hartigan's dip test, based on Martin Maechler's R package