Ryan-Rhys Griffiths (Ryan-Rhys)

Ryan-Rhys

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Company:FutureHouse Inc.

Location:San Francisco

Twitter:@ryan__rhys

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Ryan-Rhys Griffiths's repositories

The-Photoswitch-Dataset

Repository containing a benchmark dataset for machine learning property prediction of photoswitch molecules: https://pubs.rsc.org/en/content/articlehtml/2022/sc/d2sc04306h

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Constrained-Bayesian-Optimisation-for-Automatic-Chemical-Design

Code to accompany the paper "Constrained Bayesian Optimisation for Automatic Chemical Design" https://pubs.rsc.org/en/content/articlehtml/2019/sc/c9sc04026a

FlowMO

Library for training Gaussian Processes on Molecules

Language:PythonLicense:MITStargazers:36Issues:2Issues:4

Heteroscedastic-BO

Heteroscedastic Bayesian Optimisation in Numpy

Mrk_335

Modelling the Multiwavelength Variability of Mrk-335 using Gaussian processes

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PILCO

An Implementation of PILCO: Probabilistic Inference for Learning Control

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Cyg_X1

Gaussian process modelling of lightcurves from Cyg-X1

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Nanoparticle-Systems-Interaction-Potential-Computation

A collection of Python scripts for computing the interaction potential energy profiles in nanoparticle systems including, but not limited to, nanoparticle-electrode ensembles. The two principle forces accounted for in the computations are the Coulombic interactions between dissociated charge-bearing ligands functionalising the surface of the nanoparticles in addition to intrinsic van der Waals forces between the metal cores of the nanoparticles.

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Ax

Adaptive Experimentation Platform

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botorch

Bayesian optimization in PyTorch

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genedisco-starter

The starter repository for submissions to the GeneDisco challenge for optimized experimental design in genetic perturbation experiments.

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HEBO

Bayesian optimisation library developped by Huawei Noah's Ark Library

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Heteroscedastic-BayesOpt

Heteroscedastic Bayesian Optimisation in BoTorch

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noah-research

Noah Research

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papers-for-molecular-design-using-DL

List of molecular design using Generative AI and Deep Learning

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