Increasing the Scope as You Learn: Adaptive Bayesian Optimization in Nested Subspaces. - Leonard Papenmeier; Luigi Nardi; Matthias Poloczek (NeurIPS, 2022)

Bounce: Reliable High-Dimensional Bayesian Optimization for Combinatorial and Mixed Spaces. - Leonard Papenmeier; Luigi Nardi; Matthias Poloczek (NeurIPS, 2023)

Bounce: a Reliable Bayesian Optimization Algorithm for Combinatorial and Mixed Spaces. - Leonard Papenmeier; Luigi Nardi; Matthias Poloczek (CoRR, 2023)

High-dimensional Bayesian Optimization with Group Testing. - Erik Orm Hellsten; Carl Hvarfner; Leonard Papenmeier; Luigi Nardi (CoRR, 2023)

Exploring Exploration in Bayesian Optimization. - Leonard Papenmeier; Nuojin Cheng; Stephen Becker; Luigi Nardi (UAI, 2025)

A Unified Framework for Entropy Search and Expected Improvement in Bayesian Optimization. - Nuojin Cheng; Leonard Papenmeier; Stephen Becker; Luigi Nardi (CoRR, 2025)

Understanding High-Dimensional Bayesian Optimization. - Leonard Papenmeier; Matthias Poloczek; Luigi Nardi (CoRR, 2025)

Leveraging Axis-Aligned Subspaces for High-Dimensional Bayesian Optimization with Group Testing. - Erik Hellsten; Carl Hvarfner; Leonard Papenmeier; Luigi Nardi (CoRR, 2025)

Bencher: Simple and Reproducible Benchmarking for Black-Box Optimization. - Leonard Papenmeier; Luigi Nardi (CoRR, 2025)