Panoramic stitching of single cell data

Efficient evolution from protein language models

Language modeling of viral evolution

Evolutionary velocity with protein language models

Geometry-preserving random sampling

Learning with uncertainty for biological discovery and design

Multi-study integration of cellular trajectories

Realizing private and practical pharmacological collaboration

Learning mutational semantics

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Fast and memory-efficient exact attention

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Source code for "Learning protein sequence embeddings using information from structure" - ICLR 2019

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Framework for integrating heterogeneous modalities of data

Single-Cell Analysis in Python. Scales to >1M cells.

Benchmarking analysis of data integration tools

a novel DTA predition method using graph neural network

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Junction Tree Variational Autoencoder for Molecular Graph Generation (ICML 2018)

Repository for StripedHyena-7B, a state-of-the-art beyond Transformer model

A library for accelerating Transformer models on NVIDIA GPUs, including using 8-bit floating point (FP8) precision on Hopper, Ada and Blackwell GPUs, to provide better performance with lower memory utilization in both training and inference.

Ongoing research training transformer models at scale

Python package for the creation, manipulation, and learning of Causal DAGs

Example usage of https://github.com/uhlerlab/causaldag

Implementation of the Louvain algorithm for community detection with various methods for use with igraph in python.

This contains the dataset for comparing scRNA-seq analysis methods

PROSODIC: a metrical-phonological parser, written in Python. For English and Finnish, with flexible language support.

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Graph-Guided Banding of the Covariance Matrix

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Low-rank models of structured data