Aryl Halides
Optimize yield of several aryl halide cross couplings
Bayesian optimization, natural language processing, large language models, cheminformatics, materials informatics, generative models
๐โโ๏ธ The Acceleration Consortium (AC) at the University of Toronto (https://acceleration.utoronto.ca/) is a global community of academia, government, and industry members. Its purpose is to accelerate the design and discovery of a wide range of new materials and molecules, from renewable energy and consumer electronics to drugs. Using self-driving laboratories (SDLs), the AC leverages the power of artificial intelligence, robotics, engineering, and chemistry to dramatically reduce the time and cost of bringing these advanced materials to marketโfrom an average of 20 years and $100 million to as little as one year and $1 million. Recently, the AC was awarded a $200-million grant by Canada First Research Excellence Fund (CFREF) to support the development of SDLs.
The AccelerationConsortium
HuggingFace organization is intended to host datasets and models for on-demand usage, such as the optimization benchmarks for the Bayesian Optimization Hackathon for Chemistry and Materials.
Optimize yield of several aryl halide cross couplings
A 2D analytic function used for optimization benchmarking
A high-dimensional, multi-objective, multi-fidelity function
Optimize a four-dimensional transfer learning example
Simple continuous function with many irrelevant parameters
Simple function with continuous and categorical parameters