Class or Function Names ImplicitNaturalGradientSampler Example import optuna import optunahub def objective(trial: optuna.Trial) -> float: x = trial.suggest_float("x", -100, 100) y = trial.suggest_float("y", -100, 100) return x**2 + y**2 def main() -> None: mod = optunahub.load_module("samplers/implicit_natural_gradient") sampler = mod.ImplicitNaturalGradientSampler() study = optuna.create_study(sampler=sampler) study.optimize(objective, n_trials=200) print(study.best_trial.value, study.best_trial.params) if __name__ == "__main__": main() Others 📝 A Natural Gradient-Based Optimization Algorithm Registered on OptunaHub: Blog post by Hiroki Takizawa. In the post, benchmark results are presented as shown in the figure below.