simonlevine

clinical-longformer

dl-for-genomics

Selections from CS185-Deep Learning for Genomics, Brown University

fainhD

membership-query-synthesis

A look at how active learning methods could use MQS via the modAL and SDV libraries.

molecular-GNN

Predicting LogD Lipophilicity values from SMILES objects using graph-convolutional networks

baal

Library to enable Bayesian active learning in your research or labeling work.

basenji

Sequential regulatory activity predictions with deep convolutional neural networks.

singlecell-sim-by-VAE

A repository for VAE-based simulation of latent cell characteristics.

Compact-Transformers

[Preprint] Escaping the Big Data Paradigm with Compact Transformers, 2021

deepmind-research

This repository contains implementations and illustrative code to accompany DeepMind publications

DeepSilencer

A deep convolutional neural network for the accurate prediction of silencers

DNABERT

DNABERT: pre-trained Bidirectional Encoder Representations from Transformers model for DNA-language in genome

EmbeddingRecycling

Embedding Recycling for Language models

enformer-pytorch

Implementation of Enformer, Deepmind's attention network for predicting gene expression, in Pytorch

esm

Evolutionary Scale Modeling (esm): Pretrained language models for proteins

FastSK

Bioinformatics 2020: FastSK: Fast and Accurate Sequence Classification by making gkm-svm faster and scalable. https://fastsk.readthedocs.io/en/master/

genesis

Deep Exploration Networks - Diverse Deep Generative Models for DNA, RNA and Protein Sequences

h-transformer-1d

Implementation of H-Transformer-1D, Hierarchical Attention for Sequence Learning

improved_CcGAN

Continuous Conditional Generative Adversarial Networks (CcGAN)

lambo

Code to reproduce experiments in "Accelerating Bayesian Optimization for Protein Design with Denoising Autoencoders" (Stanton et al 2022)

lipophilicity-prediction

Code for "Lipophilicity Prediction with Multitask Learning and Molecular Substructures Representation" paper. Machine Learning for Molecules Workshop @ NeurIPS 2020

modAL

A modular active learning framework for Python

molgpt

MPRA-DragoNN

Code accompanying the paper "Deciphering regulatory DNA sequences and noncoding genetic variants using neural network models of massively parallel reporter assays"

Nucleic-Transformer

peft

🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.

peptimizer

Peptide optimization with Machine Learning

Swin-Transformer

This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".

Swin-Transformer-V2

PyTorch reimplementation of the paper "Swin Transformer V2: Scaling Up Capacity and Resolution" [arXiv 2021].

trl

Train transformer language models with reinforcement learning.