BetaCitation Atlas

RESEARCH PAPER · Computational Materials Science · 2022

High-dimensional Bayesian optimization of 23 hyperparameters over 100 iterations for an attention-based network to predict materials property: A case study on CrabNet using Ax platform and SAASBO

Sterling G. Baird, Marianne Liu, Taylor D. Sparks

Read original paper ↗

See where this research leads.

33 direct citing papers in this saved network. Explore the next layer with second-order citations.

Open in your workspace →Saved 2026-10-14 · complete coverage
Filter Citing Papers
Press Enter or comma to add · × to remove · searches titles and available abstracts
Journals
All journals
Most represented first · select one or more
Explore Terms In These PapersHide SuggestionsShow Suggestions

Original and current center papers stay visible as anchors.
Numbers show citations received
42 direct citing works

High-dimensional Bayesian optimization of 23 hyperparameters over 100 iterations for an attention-based network to predict materials property: A case study on CrabNet using Ax platform and SAASBOOriginalEffect of reducible and irreducible search space representations on adaptive design efficiency: a case study on maximizing packing fraction for solid rocket fuel propellant simulations2The most compact search space is not always the most efficient: A case study on maximizing solid rocket fuel packing fraction via constrained Bayesian optimization6What is a minimal working example for a self-driving laboratory?49Bayesian optimisation for efficient material discovery: a mini review49Comparative Study of Five Classifiers for Predicting Power Conversion Efficiency in Perovskite Solar Cells0Materials Science Optimization Benchmark Dataset for Multi-fidelity Hard-sphere Packing Simulations3Compactness Matters: Improving Bayesian Optimization Efficiency of Materials Formulations through Invariant Search Spaces12Materials Science Optimization Benchmark Dataset for High-dimensional, Multi-objective, Multi-fidelity Optimization of CrabNet Hyperparameters0Materials Science Optimization Benchmark Dataset for Multi-Objective, Multi-Fidelity Optimization of Hard-Sphere Packing Simulations0Stoichiometric growth of SrTiO3 films via Bayesian optimization with adaptive prior mean9Computer-assisted discovery and rational synthesis of ternary oxides3Building a “Hello World” for self-driving labs: The Closed-loop Spectroscopy Lab Light-mixing demo13Carbon Footprint of Artificial Intelligence in Materials Science: Should We Be Concerned?1Carbon Footprint of Artificial Intelligence in Materials Science: Should We Be Concerned?0Machine Learning-Assisted Large-Area Preparation of MoS2 Materials9Materials science optimization benchmark dataset for multi-objective, multi-fidelity optimization of hard-sphere packing simulations3Experimental Analysis and Machine Learning of Ground Vibrations Caused by an Elevated High-Speed Railway Based on Random Forest and Bayesian Optimization12Adaptive Hyperparameter Tuning Within Neural Network-Based Efficient Global Optimization0How the AI-assisted discovery and synthesis of a ternary oxide highlights capability gaps in materials science21Automated Hyperparameter Tuning for Airfoil Shape Optimization with Neural Network Models6Assessment of human health risk from potentially toxic elements and predicting groundwater contamination using machine learning approaches72The carbon footprint of predicting CO2 storage capacity in metal-organic frameworks within neural networks8Revolutionizing NLP: Multimodal Integration for Enhanced Image-to-Text Extraction3Self-Driving Laboratories for Chemistry and Materials Science674An Integrated FEM-AI Methodology for Predictive Modelling and Optimization of Filled Bio-Composites0Metaheuristics for the Electric Vehicle Patrol Route Planning Problem0Proof-of-concept ensemble machine-learning forecasting of tensile properties in hybrid polypropylene composites reinforced with flax, basalt, and rice husk powder2An integrated water quality assessment and its prediction utilizing the CWQI, CRITIC based-improved CWQI, sensitivity analysis, multivariate techniques, machine learning algorithms and GIS approaches to determine pollution intensities in the river basin (Odisha)2Constraint-Aware Multi-Objective Bayesian Optimization for Physical Connection Parameter Tuning in Brain–Computer Interfaces0Bayesian dual-objective optimization framework for a heterogeneous metamaterial design in aero-engine robotic grinding vibration suppression0Interpretable self-driving sputtering epitaxy reveals human-usable growth rules for β-Ga2O3 films0Coordinate-preserving degradation-knee mapping for Kriging relevance mechanisms in FFD-based hull-form optimization0LLMs as Representation Generators for Gradient‐Free Scientific Optimization: A Case Study in Battery Fast Charging0

Arrows point to the paper being cited. Selecting a paper shows its incoming citations and its known path back to the original paper.

Drag to pan · Use + / − to zoom · Escape to close43 nodes / 53 citation links
Browse Matching Papers

Papers that cite this work

33 direct citing papers saved.

  1. Effect of reducible and irreducible search space representations on adaptive design efficiency: a case study on maximizing packing fraction for solid rocket fuel propellant simulations

    ChemRxiv · 2022-05-10

    Sterling G. Baird, Jason R. Hall, Taylor D. Sparks

    Read original paper ↗ ·

  2. The most compact search space is not always the most efficient: A case study on maximizing solid rocket fuel packing fraction via constrained Bayesian optimization

    ChemRxiv · 2022-09-06

    Sterling G. Baird, Jason R. Hall, Taylor D. Sparks

    Read original paper ↗ ·

  3. What is a minimal working example for a self-driving laboratory?

    Matter · 2022-12-01

    Sterling G. Baird, Taylor D. Sparks

    Read original paper ↗ ·

  4. Bayesian optimisation for efficient material discovery: a mini review

    Nanoscale · 2023-01-01

    Yimeng Jin, Priyank V. Kumar

    Read original paper ↗ ·

  5. Comparative Study of Five Classifiers for Predicting Power Conversion Efficiency in Perovskite Solar Cells

    International Journal of convergence in healthcare · 2023-01-01

    Nita Samantaray, Anu Tonk, Arjun Singh

    Read original paper ↗ ·

  6. Materials Science Optimization Benchmark Dataset for Multi-fidelity Hard-sphere Packing Simulations

    ChemRxiv · 2023-01-09

    Sterling G. Baird, Taylor D. Sparks

    Read original paper ↗ ·

  7. Compactness Matters: Improving Bayesian Optimization Efficiency of Materials Formulations through Invariant Search Spaces

    Computational Materials Science · 2023-02-02

    Sterling G. Baird, Jason R. Hall, Taylor D. Sparks

    Read original paper ↗ ·

  8. Materials Science Optimization Benchmark Dataset for High-dimensional, Multi-objective, Multi-fidelity Optimization of CrabNet Hyperparameters

    ChemRxiv · 2023-03-07

    Sterling G. Baird, Jeet N. Parikh, Taylor D. Sparks

    Read original paper ↗ ·

  9. Materials Science Optimization Benchmark Dataset for Multi-Objective, Multi-Fidelity Optimization of Hard-Sphere Packing Simulations

    ChemRxiv · 2023-03-07

    Sterling G. Baird, Ramsey Issa, Taylor D. Sparks

    Read original paper ↗ ·

  10. Stoichiometric growth of SrTiO3 films via Bayesian optimization with adaptive prior mean

    APL Machine Learning · 2023-04-06

    Yuki K. Wakabayashi, Takuma Otsuka, Yoshiharu Krockenberger, Hiroshi Sawada, Yoshitaka Taniyasu, Hideki Yamamoto

    Read original paper ↗ ·

  11. Computer-assisted discovery and rational synthesis of ternary oxides

    ChemRxiv · 2023-04-28

    Joseph H. Montoya, Carolyn A. Grimley, Muratahan Aykol, Colin Ophus, Hadas Sternlicht, Benjamin H. Savitzky, Andrew M. Minor, Steven B. Torrisi, Jackson Goedjen, Ching‐Chang Chung, Andrew H. Comstock, Shijing Sun

    Read original paper ↗ ·

  12. Building a “Hello World” for self-driving labs: The Closed-loop Spectroscopy Lab Light-mixing demo

    STAR Protocols · 2023-05-31

    Sterling G. Baird, Taylor D. Sparks

    Read original paper ↗ ·

  13. Carbon Footprint of Artificial Intelligence in Materials Science: Should We Be Concerned?

    ChemRxiv · 2023-07-31

    Vadim Korolev, Artem A. Mitrofanov

    Read original paper ↗ ·

  14. Carbon Footprint of Artificial Intelligence in Materials Science: Should We Be Concerned?

    ChemRxiv · 2023-08-08

    Vadim Korolev, Artem A. Mitrofanov

    Read original paper ↗ ·

  15. Machine Learning-Assisted Large-Area Preparation of MoS2 Materials

    Nanomaterials · 2023-08-09

    Jingting Wang, Mingying Lu, Yongxing Chen, Guolin Hao, Bin Liu, Pinghua Tang, Lian Yu, Wen Lei, Haining Ji

    Read original paper ↗ ·

  16. Materials science optimization benchmark dataset for multi-objective, multi-fidelity optimization of hard-sphere packing simulations

    Data in Brief · 2023-08-10

    Sterling G. Baird, Ramsey Issa, Taylor D. Sparks

    Read original paper ↗ ·

  17. Experimental Analysis and Machine Learning of Ground Vibrations Caused by an Elevated High-Speed Railway Based on Random Forest and Bayesian Optimization

    Sustainability · 2023-08-23

    Yanmei Cao, Boyang Li, Qi Xiang, Yuxian Zhang

    Read original paper ↗ ·

  18. Adaptive Hyperparameter Tuning Within Neural Network-Based Efficient Global Optimization

    Lecture notes in computer science · 2024-01-01

    Taeho Jeong, Pavankumar Koratikere, Leifur Leifsson, Slawomir Marcin Koziel, Anna Pietrenko‐Dabrowska

    Read original paper ↗ ·

  19. How the AI-assisted discovery and synthesis of a ternary oxide highlights capability gaps in materials science

    Chemical Science · 2024-01-01

    Joseph H. Montoya, Carolyn A. Grimley, Muratahan Aykol, Colin Ophus, Hadas Sternlicht, Benjamin H. Savitzky, Andrew M. Minor, Steven B. Torrisi, Jackson Goedjen, Ching‐Chang Chung, Andrew H. Comstock, Shijing Sun

    Read original paper ↗ ·

  20. Automated Hyperparameter Tuning for Airfoil Shape Optimization with Neural Network Models

    AIAA SciTech Forum · 2024-01-04

    Taeho Jeong, Pavankumar Koratikere, Leifur Leifsson

    Read original paper ↗ ·

  21. Assessment of human health risk from potentially toxic elements and predicting groundwater contamination using machine learning approaches

    Journal of Contaminant Hydrology · 2024-01-21

    Md Galal Uddin, Md. Hasan Imran, Abdul Majed Sajib, Md Abu Hasan, Mir Talas Mahammad Diganta, Tomasz Dabrowski, Agnieszka I. Olbert, Md Moniruzzaman

    Read original paper ↗ ·

  22. The carbon footprint of predicting CO2 storage capacity in metal-organic frameworks within neural networks

    iScience · 2024-03-29

    Vadim Korolev, Artem A. Mitrofanov

    Read original paper ↗ ·

  23. Revolutionizing NLP: Multimodal Integration for Enhanced Image-to-Text Extraction

    International Conference on Computational Modelling, Simulation and Optimization (ICCMSO) · 2024-06-14

    Chiguru Aparna, K Rajchandar

    Read original paper ↗ ·

  24. Self-Driving Laboratories for Chemistry and Materials Science

    Chemical Reviews · 2024-08-13

    Gary Tom, Stefan P. Schmid, Sterling G. Baird, Yang Cao, Kourosh Darvish, Han Hao, Stanley Lo, Sergio Pablo‐García, Ella Miray Rajaonson, Marta Skreta, Naruki Yoshikawa, Samantha Corapi, Gun Deniz Akkoc, Felix Strieth‐Kalthoff, Martin T. Seifrid, Alán Aspuru‐Guzik

    Read original paper ↗ ·

  25. An Integrated FEM-AI Methodology for Predictive Modelling and Optimization of Filled Bio-Composites

    E3S Web of Conferences · 2025-01-01

    Maryame Lakrade, Zakaria Mighouar, Laidi Zahiri, Khalifa Mansouri

    Read original paper ↗ ·

  26. Metaheuristics for the Electric Vehicle Patrol Route Planning Problem

    SSRN Electronic Journal · 2025-01-01

    James Swedeen, Greg N. Droge

    Read original paper ↗ ·

  27. Proof-of-concept ensemble machine-learning forecasting of tensile properties in hybrid polypropylene composites reinforced with flax, basalt, and rice husk powder

    Discover Materials · 2025-11-20

    Thanh Mai Nguyen Tran, Duy Tran Quang, M. N. Prabhakar, Xiem Nguyen Thang, Jung‐il Song

    Read original paper ↗ ·

  28. An integrated water quality assessment and its prediction utilizing the CWQI, CRITIC based-improved CWQI, sensitivity analysis, multivariate techniques, machine learning algorithms and GIS approaches to determine pollution intensities in the river basin (Odisha)

    Environmental Science and Pollution Research · 2026-03-06

    Abhijeet Das

    Read original paper ↗ ·

  29. Constraint-Aware Multi-Objective Bayesian Optimization for Physical Connection Parameter Tuning in Brain–Computer Interfaces

    International Conference on Inventive Computation Technologies (ICICT) · 2026-04-15

    Hulin Jin, Zhiran Jin, Yong-Guk Kim

    Read original paper ↗ ·

  30. Bayesian dual-objective optimization framework for a heterogeneous metamaterial design in aero-engine robotic grinding vibration suppression

    Aerospace Science and Technology · 2026-08-07

    Yutong Jin, Hua Yang, Wolfgang H. Müller, Shijie Dai, Kai Li, Yang Li

    Read original paper ↗ ·

  31. Interpretable self-driving sputtering epitaxy reveals human-usable growth rules for β-Ga2O3 films

    Nature Communications · 2026-08-13

    Yuki K. Wakabayashi, Yui Ogawa, Franz Benedict Romero, Coleman Wagner, Takuma Otsuka, Yoshitaka Taniyasu

    Read original paper ↗ ·

  32. Coordinate-preserving degradation-knee mapping for Kriging relevance mechanisms in FFD-based hull-form optimization

    Ocean Engineering · 2026-09-02

    Qingwen He, Yanping He, Zhe Chen, Xin Yu, Jintao Zhou

    Read original paper ↗ ·

  33. LLMs as Representation Generators for Gradient‐Free Scientific Optimization: A Case Study in Battery Fast Charging

    Advanced Science · 2026-10-11

    Ge Lei, Ferran Brosa Planella, Sterling G. Baird, Samuel J. Cooper

    Read original paper ↗ ·
Citation Atlas · A map of research, not a ranking.