Showing 6 of 6 projects
Deep learning models for crop yield prediction using remote sensing data, with CNN/LSTM and Gaussian Process approaches.
An extremely lightweight Gaussian Process library for Python built on JAX with GPU acceleration and automatic differentiation.
A lightweight Bayesian optimization library built on JAX for efficient optimization of expensive-to-evaluate functions.
A simple yet essential Python framework for Bayesian optimization, enabling efficient hyperparameter tuning and black-box function optimization.
Composable kernels for scikit-learn implemented in JAX, enabling faster kernel computations and automatic differentiation.
SKBEL - Bayesian Evidential Learning framework built on top of scikit-learn.
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