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chemgan-challenge

Code for the paper: Benhenda, M. 2017. ChemGAN challenge for drug discovery: can AI reproduce natural chemical diversity? arXiv preprint arXiv:1708.08227.

chinese-llama-alpaca

中文LLaMA&Alpaca大语言模型+本地部署 (Chinese LLaMA & Alpaca LLMs)

dplyr

Plyr specialised for data frames: faster & with remote datastores

drug-discovery-using-gans

Check out the dash visualization at https://dash-drug-explorer.plot.ly/out

emmv_benchmarks

feature-based-similarity-search-for-time-series

Develop a novel method for fast retrieval of k-Nearest Neighbors for time series curves

forecastxgb-r-package

An R package for time series models and forecasts with xgboost compatible with {forecast} S3 classes

gentrl

Generative Tensorial Reinforcement Learning (GENTRL) model

ios

Representative subset selection and outlier detection via isolation Forest

ligan

Deep generative models for structure-based drug discovery

llama

Inference code for LLaMA models

release

Deep Reinforcement Learning for de-novo Drug Design

spark

Mirror of Apache Spark

virtual_libraries

Supporting code for the paper «Generative molecular design in low data regimes»

xgboost

Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Flink and DataFlow