GPflowOpt: A Bayesian Optimization Library using TensorFlow

GPflowOpt: A Bayesian Optimization Library using TensorFlow

10 November 2017

Papers citing "GPflowOpt: A Bayesian Optimization Library using TensorFlow"

16 / 16 papers shown

Title
AutoML in Heavily Constrained Applications Felix Neutatz Marius Lindauer Ziawasch Abedjan 30 4 0 29 Jun 2023
OpenBox: A Python Toolkit for Generalized Black-box Optimization Huaijun Jiang Yu Shen Yang Li Beicheng Xu Sixian Du Wentao Zhang Ce Zhang Bin Cui 38 5 0 26 Apr 2023
Trieste: Efficiently Exploring The Depths of Black-box Functions with TensorFlow Victor Picheny Joel Berkeley Henry B. Moss Hrvoje Stojić Uri Granta ... Sergio Pascual-Diaz Stratis Markou Jixiang Qing Nasrulloh Loka Ivo Couckuyt 31 17 0 16 Feb 2023
Unleashing the Potential of Acquisition Functions in High-Dimensional Bayesian Optimization Jiayu Zhao Renyu Yang Shenghao Qiu Zheng Wang 24 4 0 16 Feb 2023
Multi-Objective Hyperparameter Optimization in Machine Learning -- An Overview Florian Karl Tobias Pielok Julia Moosbauer Florian Pfisterer Stefan Coors ... Jakob Richter Michel Lang Eduardo C. Garrido-Merchán Juergen Branke B. Bischl AI4CE 26 57 0 15 Jun 2022
Designing Robust Biotechnological Processes Regarding Variabilities using Multi-Objective Optimization Applied to a Biopharmaceutical Seed Train Design T. H. Rodríguez Anton Sekulic Markus Lange-Hegermann Björn Frahm 18 9 0 06 May 2022
Emulation of physical processes with Emukit Andrei Paleyes Mark Pullin Maren Mahsereci Cliff McCollum Neil D. Lawrence Javier I. González 28 79 0 25 Oct 2021
Bayesian Optimization is Superior to Random Search for Machine Learning Hyperparameter Tuning: Analysis of the Black-Box Optimization Challenge 2020 Ryan Turner David Eriksson M. McCourt J. Kiili Eero Laaksonen Zhen Xu Isabelle M Guyon BDL 30 289 0 20 Apr 2021
Revisiting Bayesian Optimization in the light of the COCO benchmark Rodolphe Le Riche Victor Picheny 27 26 0 30 Mar 2021
Amazon SageMaker Automatic Model Tuning: Scalable Gradient-Free Optimization Valerio Perrone Huibin Shen Aida Zolic I. Shcherbatyi Amr Ahmed ... Barbara Pogorzelska Miroslav Miladinovic K. Kenthapadi Matthias Seeger Cédric Archambeau 45 16 0 15 Dec 2020
HEBO Pushing The Limits of Sample-Efficient Hyperparameter Optimisation Alexander I. Cowen-Rivers Wenlong Lyu Rasul Tutunov Zhi Wang Antoine Grosnit ... A. Maraval Hao Jianye Jun Wang Jan Peters H. Ammar 27 74 0 07 Dec 2020
On Hyperparameter Optimization of Machine Learning Algorithms: Theory and Practice Li Yang Abdallah Shami AI4CE 25 2,033 0 30 Jul 2020
BoTorch: A Framework for Efficient Monte-Carlo Bayesian Optimization Maximilian Balandat Brian Karrer Daniel R. Jiang Sam Daulton Benjamin Letham A. Wilson E. Bakshy 32 93 0 14 Oct 2019
Bayesian Optimization Meets Riemannian Manifolds in Robot Learning Noémie Jaquier Leonel Rozo Sylvain Calinon Mathias Bürger 17 53 0 11 Oct 2019
Learning search spaces for Bayesian optimization: Another view of hyperparameter transfer learning Valerio Perrone Huibin Shen Matthias Seeger Cédric Archambeau Rodolphe Jenatton 27 96 0 27 Sep 2019
Max-value Entropy Search for Efficient Bayesian Optimization Zi Wang Stefanie Jegelka 110 404 0 06 Mar 2017