Examples

This page consists of code examples on how to use DeepHyper.

Black-box optimization

Generating Combinations of Parameters for Standard Experimental Designs

Generating Combinations of Parameters for Standard Experimental Designs

Mutli-Objective Black-Box Optimization

Mutli-Objective Black-Box Optimization

Black-Box Optimization

Black-Box Optimization

Noisy Black-Box Optimization

Noisy Black-Box Optimization

Constrained Black-Box Optimization with Rejection Sampling

Constrained Black-Box Optimization with Rejection Sampling

Learn to Avoid Failures with Bayesian Optimization

Learn to Avoid Failures with Bayesian Optimization

Using Transfer Learning to Speed-up Bayesian Optimization

Using Transfer Learning to Speed-up Bayesian Optimization

Constrained Black-Box Optimization with Custom Sampler

Constrained Black-Box Optimization with Custom Sampler

Hyperparameter optimization

Hyperparameter search for text classification

Hyperparameter search for text classification

Hyperparameter Optimization for Text Classification with Early Discarding

Hyperparameter Optimization for Text Classification with Early Discarding

Hyperparameter optimization and overfitting

Hyperparameter optimization and overfitting

Parallelism

Managing Queued Compute Resources Using Evaluator and MPI Executables

Managing Queued Compute Resources Using Evaluator and MPI Executables

Profile the Worker Utilization

Profile the Worker Utilization

From Sequential to Massively-Parallel Bayesian Optimization

From Sequential to Massively-Parallel Bayesian Optimization

Scaling Bayesian Optimization with Heterogeneous Parallelism

Scaling Bayesian Optimization with Heterogeneous Parallelism

Uncertainty quantification

Hyperparameter Optimized Ensemble of Random Decision Trees with Uncertainty for Classification

Hyperparameter Optimized Ensemble of Random Decision Trees with Uncertainty for Classification

Neural Architecture Search and Deep Ensemble with Uncertainty Quantification for Regression (Pytorch)

Neural Architecture Search and Deep Ensemble with Uncertainty Quantification for Regression (Pytorch)