Max Shen

iap-cidl. Causal Inference & Deep Learning, MIT IAP 2018

inDelphi-model. Predictive model for CRISPR-mediated DNA repair outcomes through NHEJ/MMEJ, built with machine learning

iap-appbml. Applied Probabilistic Programming & Bayesian Machine Learning (MIT IAP 2017)

gflownet. Python

piu-analysis. Platform for pump it up data analysis

indelphi-dataprocessinganalysis. Data Processing, Modeling and Analysis scripts for CRISPR-inDelphi

inDelphi-app. Heroku/Dash app for inDelphi.

be_predict_bystander. Deep conditional autoregressive models for genome editing sequence-to-sequence problems

be_predict_efficiency. Python

evoracle. A method for reconstructing frequency trajectories and fitnesses of long genotypes from short read data from directed evolution timepoints.

piu-vis-ss. TypeScript

piu-annotate. Jupyter Notebook

hackerargs. Configurable options in 1 line of code

piu-app. JavaScript

be-modeling. Code used for training BE-Hive models

baseedit-app. Heroku web app with Dash Plotly

lib-analysis. Python

mylib. A collection of generically useful scripts and functions

evoracle-dataprocessinganalysis. Jupyter Notebook

latent-multiGP-inference. Joint inference of 10 latent Gaussian processes on time series data with latent stochastic weekend/holiday/Covid effectsGPyTorch and Pyro