Pinned Repositories
ai4sci-2021-denovo-benchmarks
Code for workshop paper "A Fresh Look at De Novo Molecular Design Benchmarks" at the NeurIPS AI for Science NeurIPS 2021 Workshop
basic-mol-bo-workshop2024
Proof of concept molecule BO
book-summaries
Summaries of books I have read
linux-setup
Shell scripts to set up a new Linux computer the way I like it.
mol_ga
Simple, lightweight package for genetic algorithms on molecules
nn-quine
Implementation of neural network quine (https://arxiv.org/abs/1803.05859)
retro-fallback-iclr24
Official code to accompany the ICLR 2024 paper "Retro-fallback: retrosynthetic planning in an uncertain world"
tanimoto-random-features-neurips23
Official code to accompany the NeurIPS 2023 paper "Tanimoto Random Features for Scalable Molecular Machine Learning"
dockstring
A Python package for molecular docking with an extensive, highly-curated dataset and a set of realistic benchmark tasks for drug discovery.
syntheseus
Package for Retrosynthetic Planning
AustinT's Repositories
AustinT/mol_ga
Simple, lightweight package for genetic algorithms on molecules
AustinT/basic-mol-bo-workshop2024
Proof of concept molecule BO
AustinT/retro-fallback-iclr24
Official code to accompany the ICLR 2024 paper "Retro-fallback: retrosynthetic planning in an uncertain world"
AustinT/seed-mobo-for-molecules
Seed repository for multi-objective BO over molecule space
AustinT/book-summaries
Summaries of books I have read
AustinT/kernel-only-GP
Tiny package for GPs using the kernel matrix as inputs
AustinT/tanimoto-gp
Small library for Tanimoto-kernel Gaussian processes
AustinT/rough-tanimoto-jax
Trial implementation of Tanimoto Kernels + Random features in Jax
AustinT/syntheseus
Personal copy of syntheseus for experimental development
AustinT/syntheseus-retro-star-benchmark
Syntheseus wrapper for retro* benchmark (by Chen et al, 2020)
AustinT/linux-setup
Shell scripts to set up a new Linux computer the way I like it.
AustinT/tanimoto-random-features-neurips23
Official code to accompany the NeurIPS 2023 paper "Tanimoto Random Features for Scalable Molecular Machine Learning"
AustinT/2023-iclr-adkf-visuals
Visualization code for ADKF ICLR Video
AustinT/AustinT
My GitHub profile
AustinT/AustinT.github.io
Personal website
AustinT/code-anon-check
Script(s) to check whether code is anonymous.
AustinT/dev-tanimoto-random-features
AustinT/gauche
A Library for Gaussian Processes in Chemistry
AustinT/harvard-cep-dataset
A repo for storing and preprocessing the entire harvard CEP dataset in a reproducible way.
AustinT/init-assistive-choice-bandits
Initial experiments about assistive choice bandits
AustinT/ml-conference-paper-scraping
Some Jupyter notebooks I used to scrape papers, and find authors with certain expertise
AustinT/MolScore
An automated scoring function to facilitate and standardize the evaluation of goal-directed generative models for de novo molecular design
AustinT/molstove
AustinT/my_pmo_benchmark_fork
AustinT/pretrained-reaction-models
Some single-step reaction models used for retrosynthetic planning.
AustinT/python-template
Template repository for python projects with pre-commit, gitignore, and flake8 formatting set up.
AustinT/rough-adkf-jax
Initial implementation of ADKF GP fitting in Jax
AustinT/rough-pdvn-training
First attempt at writing a training loop for PDVN.
AustinT/staged-recipes
A place to submit conda recipes before they become fully fledged conda-forge feedstocks
AustinT/syntheseus-paroutes
Syntheseus wrapper for PaRoutes benchmark.