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cpa icon cpa

The Compositional Perturbation Autoencoder (CPA) is a deep generative framework to learn effects of perturbations at the single-cell level. CPA performs OOD predictions of unseen combinations of drugs, learns interpretable embeddings, estimates dose-response curves, and provides uncertainty estimates.

go.gotools icon go.gotools

go tools and packages for manipulating and searching go source code

go.lib icon go.lib

cloudeng.io/go.lib - generally useful libraries and applications in go

go.pkgs icon go.pkgs

go.pkg contains a set of broadly useful go packages.

idu icon idu

idu (incremental du) gathers file system usage statistics (simular to du) storing them in a database to support incremental updates and with support for cloud filesytems.

lightning icon lightning

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

pytorch icon pytorch

Tensors and Dynamic neural networks in Python with strong GPU acceleration

ray icon ray

Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a toolkit of libraries (Ray AIR) for accelerating ML workloads.

scvi-tools icon scvi-tools

Deep probabilistic analysis of single-cell omics data

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