Walz, David

5 publications

MLOSS 2025 BoFire: Bayesian Optimization Framework Intended for Real Experiments Johannes P. Dürholt, Thomas S. Asche, Johanna Kleinekorte, Gabriel Mancino-Ball, Benjamin Schiller, Simon Sung, Julian Keupp, Aaron Osburg, Toby Boyne, Ruth Misener, Rosona Eldred, Chrysoula Kappatou, Robert M. Lee, Dominik Linzner, Wagner Steuer Costa, David Walz, Niklas Wulkow, Behrang Shafei

NeurIPS 2023 Optimizing over Trained GNNs via Symmetry Breaking Shiqiang Zhang, Juan Campos, Christian Feldmann, David Walz, Frederik Sandfort, Miriam Mathea, Calvin Tsay, Ruth Misener

NeurIPSW 2023 Practical Path-Based Bayesian Optimization Jose Pablo Folch, James A C Odgers, Shiqiang Zhang, Robert Matthew Lee, Behrang Shafei, David Walz, Calvin Tsay, Mark van der Wilk, Ruth Misener

NeurIPS 2022 SnAKe: Bayesian Optimization with Pathwise Exploration Jose Pablo Folch, Shiqiang Zhang, Robert Lee, Behrang Shafei, David Walz, Calvin Tsay, Mark van der Wilk, Ruth Misener

NeurIPS 2022 Tree Ensemble Kernels for Bayesian Optimization with Known Constraints over Mixed-Feature Spaces Alexander Thebelt, Calvin Tsay, Robert Lee, Nathan Sudermann-Merx, David Walz, Behrang Shafei, Ruth Misener