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Olympus: a benchmarking framework for noisy optimization and experiment
  planning

Olympus: a benchmarking framework for noisy optimization and experiment planning

8 October 2020
Florian Hase
Matteo Aldeghi
Riley J. Hickman
L. Roch
M. Christensen
Elena Liles
J. Hein
Alán Aspuru-Guzik
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Papers citing "Olympus: a benchmarking framework for noisy optimization and experiment planning"

16 / 16 papers shown
Title
GOLLuM: Gaussian Process Optimized LLMs -- Reframing LLM Finetuning through Bayesian Optimization
GOLLuM: Gaussian Process Optimized LLMs -- Reframing LLM Finetuning through Bayesian Optimization
Bojana Ranković
P. Schwaller
BDL
172
0
0
08 Apr 2025
Posterior Sampling-Based Bayesian Optimization with Tighter Bayesian
  Regret Bounds
Posterior Sampling-Based Bayesian Optimization with Tighter Bayesian Regret Bounds
Shion Takeno
Yu Inatsu
Masayuki Karasuyama
Ichiro Takeuchi
34
6
0
07 Nov 2023
MetaBox: A Benchmark Platform for Meta-Black-Box Optimization with
  Reinforcement Learning
MetaBox: A Benchmark Platform for Meta-Black-Box Optimization with Reinforcement Learning
Zeyuan Ma
Hongshu Guo
Jiacheng Chen
Zhenrui Li
Guojun Peng
Yue-jiao Gong
Yining Ma
Zhiguang Cao
OffRL
32
25
0
12 Oct 2023
PyPop7: A Pure-Python Library for Population-Based Black-Box
  Optimization
PyPop7: A Pure-Python Library for Population-Based Black-Box Optimization
Qiqi Duan
Guochen Zhou
Chang Shao
Zhuowei Wang
Mingyang Feng
Yuwei Huang
Yajing Tan
Yijun Yang
Qi Zhao
Yuhui Shi
31
5
0
12 Dec 2022
GAUCHE: A Library for Gaussian Processes in Chemistry
GAUCHE: A Library for Gaussian Processes in Chemistry
Ryan-Rhys Griffiths
Leo Klarner
Henry B. Moss
Aditya Ravuri
Sang T. Truong
...
A. Lee
Bingqing Cheng
Alán Aspuru-Guzik
P. Schwaller
Jian Tang
GP
30
40
0
06 Dec 2022
Graph Machine Learning for Design of High-Octane Fuels
Graph Machine Learning for Design of High-Octane Fuels
Jan G. Rittig
Martin Ritzert
Artur M. Schweidtmann
Stefanie Winkler
Jana M. Weber
P. Morsch
K. Heufer
Martin Grohe
Alexander Mitsos
Manuel Dahmen
20
23
0
01 Jun 2022
Bayesian optimization with known experimental and design constraints for
  chemistry applications
Bayesian optimization with known experimental and design constraints for chemistry applications
Riley J. Hickman
Matteo Aldeghi
Florian Hase
A. Aspuru‐Guzik
13
21
0
29 Mar 2022
Opportunities for Machine Learning to Accelerate Halide Perovskite
  Commercialization and Scale-Up
Opportunities for Machine Learning to Accelerate Halide Perovskite Commercialization and Scale-Up
Rishi E. Kumar
A. Tiihonen
Shijing Sun
D. Fenning
Zhe Liu
Tonio Buonassisi
25
10
0
08 Oct 2021
Machine Learning with Knowledge Constraints for Process Optimization of
  Open-Air Perovskite Solar Cell Manufacturing
Machine Learning with Knowledge Constraints for Process Optimization of Open-Air Perovskite Solar Cell Manufacturing
Zhe Liu
Nicholas Rolston
Austin C. Flick
T. Colburn
Zekun Ren
R. Dauskardt
Tonio Buonassisi
29
116
0
01 Oct 2021
HPOBench: A Collection of Reproducible Multi-Fidelity Benchmark Problems
  for HPO
HPOBench: A Collection of Reproducible Multi-Fidelity Benchmark Problems for HPO
Katharina Eggensperger
Philip Muller
Neeratyoy Mallik
Matthias Feurer
René Sass
Aaron Klein
Noor H. Awad
Marius Lindauer
Frank Hutter
46
100
0
14 Sep 2021
Benchmarking the Performance of Bayesian Optimization across Multiple
  Experimental Materials Science Domains
Benchmarking the Performance of Bayesian Optimization across Multiple Experimental Materials Science Domains
Qiaohao Liang
Aldair E. Gongora
Zekun Ren
A. Tiihonen
Zhe Liu
...
K. Hippalgaonkar
Benji Maruyama
Keith A. Brown
John W Fisher Iii
Tonio Buonassisi
35
118
0
23 May 2021
Golem: An algorithm for robust experiment and process optimization
Golem: An algorithm for robust experiment and process optimization
Matteo Aldeghi
Florian Hase
Riley J. Hickman
Isaac Tamblyn
Alán Aspuru-Guzik
27
22
0
05 Mar 2021
Gemini: Dynamic Bias Correction for Autonomous Experimentation and
  Molecular Simulation
Gemini: Dynamic Bias Correction for Autonomous Experimentation and Molecular Simulation
Riley J. Hickman
Florian Hase
L. Roch
Alán Aspuru-Guzik
12
4
0
05 Mar 2021
Gryffin: An algorithm for Bayesian optimization of categorical variables
  informed by expert knowledge
Gryffin: An algorithm for Bayesian optimization of categorical variables informed by expert knowledge
Florian Hase
Matteo Aldeghi
Riley J. Hickman
L. Roch
Alán Aspuru-Guzik
47
104
0
26 Mar 2020
Achieving Robustness to Aleatoric Uncertainty with Heteroscedastic
  Bayesian Optimisation
Achieving Robustness to Aleatoric Uncertainty with Heteroscedastic Bayesian Optimisation
Ryan-Rhys Griffiths
Alexander A. Aldrick
Miguel García-Ortegón
Vidhi R. Lalchand
A. Lee
31
35
0
17 Oct 2019
MoleculeNet: A Benchmark for Molecular Machine Learning
MoleculeNet: A Benchmark for Molecular Machine Learning
Zhenqin Wu
Bharath Ramsundar
Evan N. Feinberg
Joseph Gomes
C. Geniesse
Aneesh S. Pappu
K. Leswing
Vijay S. Pande
OOD
199
1,778
0
02 Mar 2017
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