AustinT

AustinT's Stars

• junegunn/fzf

  :cherry_blossom: A command-line fuzzy finder

  Language:Go64.2k3932.8k2.4k

• tmux/tmux

  tmux source code

  Language:C34.8k4273.4k2.1k

• zotero/zotero

  Zotero is a free, easy-to-use tool to help you collect, organize, annotate, cite, and share your research sources.

  Language:JavaScript10.1k1353.4k747

• cornellius-gp/gpytorch

  A highly efficient implementation of Gaussian Processes in PyTorch

  Language:Python3.5k581.3k556

• pytorch/botorch

  Bayesian optimization in PyTorch

  Language:Jupyter Notebook3.1k51520392

• sylvainhalle/textidote

  Spelling, grammar and style checking on LaTeX documents

  Language:Java927720468

• kks32/phd-thesis-template

  A LaTeX / XeLaTeX / LuaLaTeX PhD thesis template for Cambridge University Engineering Department (CUED)

  Language:TeX82646228397

• VincentStimper/normalizing-flows

  PyTorch implementation of normalizing flow models

  Language:Python6871441105

• ysig/GraKeL

  A scikit-learn compatible library for graph kernels

  Language:Python593108597

• microsoft/molecule-generation

  Implementation of MoLeR: a generative model of molecular graphs which supports scaffold-constrained generation

  Language:Python264113943

• maabuu/posebusters

  Plausibility checks for generated molecule poses.

  Language:Python21331913

• BayesWatch/deep-kernel-transfer

  Official pytorch implementation of the paper "Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels" (NeurIPS 2020)

  Language:Python197141929

• wenhao-gao/mol_opt

  Language:Python17381137

• microsoft/FS-Mol

  FS-Mol is A Few-Shot Learning Dataset of Molecules, containing molecular compounds with measurements of activity against a variety of protein targets. The dataset is presented with a model evaluation benchmark which aims to drive few-shot learning research in the domain of molecules and graph-structured data.

  Language:Python15812924

• dockstring/dockstring

  A Python package for molecular docking with an extensive, highly-curated dataset and a set of realistic benchmark tasks for drug discovery.

  Language:Python1531012030

• greglandrum/rdkit_blog

  RDKit related blog posts, notebooks, and data.

  Language:Jupyter Notebook117171243

• microsoft/syntheseus

  Package for Retrosynthetic Planning

  Language:Python11111715

• EBjerrum/scikit-mol

  scikit-learn classes for molecular vectorization using RDKit

  Language:Jupyter Notebook10441317

• molecularinformatics/Computational-ADME

  Language:Python703513

• MolecularAI/PaRoutes

  Home of the PaRoutes framework for benchmarking multi-step retrosynthesis predictions.

  Language:Python68527

• AustinT/mol_ga

  Simple, lightweight package for genetic algorithms on molecules

  Language:Python43133

• sungsoo-ahn/genetic-expert-guided-learning

  Language:Python322114

• joneswack/dp-rfs

  This repository contains PyTorch implementations of various random feature maps for dot product kernels.

  Language:Jupyter Notebook17222

• dockstring/benchmarks

  Official repository for dockstring-based benchmarks.

  Language:Jupyter Notebook6111

• dockstring/dataset

  Code to help download and extract the dockstring dataset.

  Language:Jupyter Notebook41

• kenzaxtazi/icml23-gpframe

  Code and data for 'Beyond Intuition, a Framework for Applying GPs to Real-World Data' presented at the Structured Probabilistic Inference and Generative Modeling Workshop at ICML 2023.

  Language:Jupyter Notebook40

• saitcakmak/gp-sampling

  j-wilson/GPflowSampling implemented on torch ecosystem

  Language:Jupyter Notebook4201

• schwallergroup/bochemian

  Language:Python3100

• jakepstroud/plotting_in_python

  Style sheet and plotting example script

  Language:Python21

• bbaillif/bbaillif.github.io

  Code that'll help you kickstart a personal website that showcases your work as a software developer.

  Language:HTML10