BBOmix: A Tabular Benchmark for Hyperparameter Optimization of Unsupervised Biological Representation Learning
Researchers have introduced BBOmix, a new open-source tabular benchmark designed to aid in the hyperparameter optimization of unsupervised learning models for biological data. This benchmark features over 105,000 evaluations across various autoencoder architectures and multi-omics datasets, aiming to bridge the gap between reconstruction loss and actual downstream task performance. BBOmix also provides a baseline evaluation of current hyperparameter optimization methods in this specialized domain. AI
IMPACT Provides a standardized benchmark to accelerate research in unsupervised biological representation learning and hyperparameter optimization.